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14
.github/workflows/ci.yml
vendored
14
.github/workflows/ci.yml
vendored
@@ -20,18 +20,22 @@ jobs:
|
||||
contents: read
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: Install Nix
|
||||
uses: DeterminateSystems/nix-installer-action@main
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Set up Go
|
||||
uses: actions/setup-go@v5
|
||||
uses: actions/setup-go@v6
|
||||
with:
|
||||
go-version-file: ./go.mod
|
||||
|
||||
- name: Run tests
|
||||
run: go test -v ./...
|
||||
|
||||
- name: Check for modernization opportunities
|
||||
run: |
|
||||
go run golang.org/x/tools/go/analysis/passes/modernize/cmd/modernize@latest ./...
|
||||
|
||||
- name: Install Nix
|
||||
uses: DeterminateSystems/nix-installer-action@v21
|
||||
|
||||
- name: Check Formatting
|
||||
run: nix flake check
|
||||
|
||||
4
.github/workflows/patterns.yaml
vendored
4
.github/workflows/patterns.yaml
vendored
@@ -11,7 +11,7 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v5
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
@@ -32,7 +32,7 @@ jobs:
|
||||
|
||||
- name: Upload Patterns Artifact
|
||||
if: steps.check-changes.outputs.changes == 'true'
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
name: patterns
|
||||
path: patterns.zip
|
||||
|
||||
8
.github/workflows/release.yml
vendored
8
.github/workflows/release.yml
vendored
@@ -15,12 +15,12 @@ jobs:
|
||||
contents: read
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v5
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Set up Go
|
||||
uses: actions/setup-go@v5
|
||||
uses: actions/setup-go@v6
|
||||
with:
|
||||
go-version-file: ./go.mod
|
||||
|
||||
@@ -37,11 +37,11 @@ jobs:
|
||||
contents: write
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v5
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
- name: Set up Go
|
||||
uses: actions/setup-go@v5
|
||||
uses: actions/setup-go@v6
|
||||
with:
|
||||
go-version-file: ./go.mod
|
||||
- name: Run GoReleaser
|
||||
|
||||
@@ -24,17 +24,17 @@ concurrency:
|
||||
jobs:
|
||||
update-version:
|
||||
if: >
|
||||
${{ github.repository_owner == 'danielmiessler' }} &&
|
||||
github.repository_owner == 'danielmiessler' &&
|
||||
github.event_name == 'push' && github.ref == 'refs/heads/main'
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v5
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Install Nix
|
||||
uses: DeterminateSystems/nix-installer-action@main
|
||||
uses: DeterminateSystems/nix-installer-action@v21
|
||||
|
||||
- name: Set up Git
|
||||
run: |
|
||||
|
||||
4
.vscode/settings.json
vendored
4
.vscode/settings.json
vendored
@@ -24,6 +24,7 @@
|
||||
"compadd",
|
||||
"compdef",
|
||||
"compinit",
|
||||
"conceptmap",
|
||||
"creatordate",
|
||||
"curcontext",
|
||||
"custompatterns",
|
||||
@@ -95,6 +96,7 @@
|
||||
"joho",
|
||||
"kballard",
|
||||
"Keploy",
|
||||
"kimi",
|
||||
"Kore",
|
||||
"ksylvan",
|
||||
"Langdock",
|
||||
@@ -150,6 +152,7 @@
|
||||
"Pulcherrima",
|
||||
"pycache",
|
||||
"pyperclip",
|
||||
"qwen",
|
||||
"readystream",
|
||||
"restapi",
|
||||
"rmextension",
|
||||
@@ -163,6 +166,7 @@
|
||||
"sess",
|
||||
"sgaunet",
|
||||
"shellquote",
|
||||
"skeletonlabs",
|
||||
"SSEHTTP",
|
||||
"storer",
|
||||
"Streamlit",
|
||||
|
||||
165
CHANGELOG.md
165
CHANGELOG.md
@@ -1,5 +1,170 @@
|
||||
# Changelog
|
||||
|
||||
## v1.4.349 (2025-12-16)
|
||||
|
||||
### PR [#1877](https://github.com/danielmiessler/Fabric/pull/1877) by [ksylvan](https://github.com/ksylvan): modernize: update GitHub Actions and modernize Go code
|
||||
|
||||
- Modernize GitHub Actions and Go code with latest stdlib features
|
||||
- Upgrade GitHub Actions to latest versions (v6, v21) and add modernization check step
|
||||
- Replace strings manipulation with `strings.CutPrefix` and `strings.CutSuffix`
|
||||
- Replace manual loops with `slices.Contains` for validation and use `strings.SplitSeq` for iterator-based splitting
|
||||
- Replace `fmt.Sprintf` with `fmt.Appendf` for efficiency and simplify padding calculation with `max` builtin
|
||||
|
||||
## v1.4.348 (2025-12-16)
|
||||
|
||||
### PR [#1876](https://github.com/danielmiessler/Fabric/pull/1876) by [ksylvan](https://github.com/ksylvan): modernize Go code with TypeFor and range loops
|
||||
|
||||
- Replace reflect.TypeOf with TypeFor generic syntax for improved type handling
|
||||
- Convert traditional for loops to range-based iterations for better code readability
|
||||
- Simplify reflection usage in CLI flag handling to reduce complexity
|
||||
- Update test loops to use range over integers for cleaner test code
|
||||
- Refactor string processing loops in template plugin to use modern Go patterns
|
||||
|
||||
## v1.4.347 (2025-12-16)
|
||||
|
||||
### PR [#1875](https://github.com/danielmiessler/Fabric/pull/1875) by [ksylvan](https://github.com/ksylvan): modernize: update benchmarks to use b.Loop and refactor map copying
|
||||
|
||||
- Updated benchmark loops to use cleaner `b.Loop()` syntax
|
||||
- Removed unnecessary `b.ResetTimer()` call in token benchmark
|
||||
- Used `maps.Copy` for merging variables in patterns handler
|
||||
|
||||
## v1.4.346 (2025-12-16)
|
||||
|
||||
### PR [#1874](https://github.com/danielmiessler/Fabric/pull/1874) by [ksylvan](https://github.com/ksylvan): refactor: replace interface{} with any across codebase
|
||||
|
||||
- Part 1 of dealing with #1873 as pointed out by @philoserf
|
||||
- Replace `interface{}` with `any` in slice type declarations throughout the codebase
|
||||
- Update map types from `map[string]interface{}` to `map[string]any` for modern Go standards
|
||||
- Change variadic function parameters to use `...any` instead of `...interface{}`
|
||||
- Modernize JSON unmarshaling variables to use `any` for consistency
|
||||
- Update struct fields and method signatures to prefer the `any` alias over legacy interface syntax
|
||||
|
||||
## v1.4.345 (2025-12-15)
|
||||
|
||||
### PR [#1870](https://github.com/danielmiessler/Fabric/pull/1870) by [ksylvan](https://github.com/ksylvan): Web UI: upgrade pdfjs and add SSR-safe dynamic PDF worker init
|
||||
|
||||
- Upgrade `pdfjs-dist` to v5 with new engine requirement
|
||||
- Dynamically import PDF.js to avoid SSR import-time crashes
|
||||
- Configure PDF worker via CDN using runtime PDF.js version
|
||||
- Update PDF conversion pipeline to use lazy initialization
|
||||
- Guard chat message localStorage persistence behind browser checks
|
||||
|
||||
## v1.4.344 (2025-12-14)
|
||||
|
||||
### PR [#1867](https://github.com/danielmiessler/Fabric/pull/1867) by [jaredmontoya](https://github.com/jaredmontoya): chore: update flake
|
||||
|
||||
- Chore: update flake
|
||||
- Merge branch 'main' into update-flake
|
||||
|
||||
## v1.4.343 (2025-12-14)
|
||||
|
||||
### PR [#1829](https://github.com/danielmiessler/Fabric/pull/1829) by [dependabo](https://github.com/apps/dependabot): chore(deps): bump js-yaml from 4.1.0 to 4.1.1 in /web in the npm_and_yarn group across 1 directory
|
||||
|
||||
- Updated js-yaml dependency from version 4.1.0 to 4.1.1 in the /web directory
|
||||
|
||||
## v1.4.342 (2025-12-13)
|
||||
|
||||
### PR [#1866](https://github.com/danielmiessler/Fabric/pull/1866) by [ksylvan](https://github.com/ksylvan): fix: write CLI and streaming errors to stderr
|
||||
|
||||
- Fix: write CLI and streaming errors to stderr
|
||||
- Route CLI execution errors to standard error output
|
||||
- Print Anthropic stream errors to stderr consistently
|
||||
- Add os import to support stderr error writes
|
||||
- Preserve help-output suppression and exit behavior
|
||||
|
||||
## v1.4.341 (2025-12-10)
|
||||
|
||||
### PR [#1860](https://github.com/danielmiessler/Fabric/pull/1860) by [ksylvan](https://github.com/ksylvan): fix: allow resetting required settings without validation errors
|
||||
|
||||
- Fix: allow resetting required settings without validation errors
|
||||
- Update `Ask` to detect reset command and bypass validation
|
||||
- Refactor `OnAnswer` to support new `isReset` parameter logic
|
||||
- Invoke `ConfigureCustom` in `Setup` to avoid redundant re-validation
|
||||
- Add unit tests ensuring required fields can be reset
|
||||
|
||||
## v1.4.340 (2025-12-08)
|
||||
|
||||
### PR [#1856](https://github.com/danielmiessler/Fabric/pull/1856) by [ksylvan](https://github.com/ksylvan): Add support for new ClaudeHaiku 4.5 models
|
||||
|
||||
- Add support for new ClaudeHaiku models in client
|
||||
- Add `ModelClaudeHaiku4_5` to supported models
|
||||
- Add `ModelClaudeHaiku4_5_20251001` to supported models
|
||||
|
||||
## v1.4.339 (2025-12-08)
|
||||
|
||||
### PR [#1855](https://github.com/danielmiessler/Fabric/pull/1855) by [ksylvan](https://github.com/ksylvan): feat: add image attachment support for Ollama vision models
|
||||
|
||||
- Add multi-modal image support to Ollama client
|
||||
- Implement convertMessage to handle multi-content chat messages
|
||||
- Add loadImageBytes to fetch images from URLs
|
||||
- Support base64 data URLs for inline images
|
||||
- Handle HTTP image URLs with context propagation
|
||||
|
||||
## v1.4.338 (2025-12-04)
|
||||
|
||||
### PR [#1852](https://github.com/danielmiessler/Fabric/pull/1852) by [ksylvan](https://github.com/ksylvan): Add Abacus vendor for ChatLLM models with static model list
|
||||
|
||||
- Add static model support and register Abacus provider
|
||||
- Detect modelsURL starting with 'static:' and route appropriately
|
||||
- Implement getStaticModels returning curated Abacus model list
|
||||
- Register Abacus provider with ModelsURL 'static:abacus'
|
||||
- Extend provider tests to include Abacus existence
|
||||
|
||||
## v1.4.337 (2025-12-04)
|
||||
|
||||
### PR [#1851](https://github.com/danielmiessler/Fabric/pull/1851) by [ksylvan](https://github.com/ksylvan): Add Z AI provider and glm model support
|
||||
|
||||
- Add Z AI provider configuration to ProviderMap
|
||||
- Include BaseURL for Z AI API endpoint
|
||||
- Add test case for Z AI provider existence
|
||||
- Add glm to OpenAI model prefixes list
|
||||
- Support new Z AI provider in OpenAI compatible plugins
|
||||
|
||||
## v1.4.336 (2025-12-01)
|
||||
|
||||
### PR [#1848](https://github.com/danielmiessler/Fabric/pull/1848) by [zeddy303](https://github.com/zeddy303): Fix localStorage SSR error in favorites-store
|
||||
|
||||
- Fix localStorage SSR error in favorites-store by using SvelteKit's browser constant instead of typeof localStorage check to properly handle server-side rendering and prevent 'localStorage.getItem is not a function' error when running dev server
|
||||
|
||||
## v1.4.335 (2025-11-28)
|
||||
|
||||
### PR [#1847](https://github.com/danielmiessler/Fabric/pull/1847) by [ksylvan](https://github.com/ksylvan): Improve model name matching for NeedsRaw in Ollama plugin
|
||||
|
||||
- Improved model name matching in Ollama plugin by replacing prefix-based matching with substring matching
|
||||
- Enhanced NeedsRaw functionality to support more flexible model name detection
|
||||
- Renamed `ollamaPrefixes` variable to `ollamaSearchStrings` for better code clarity
|
||||
- Replaced `HasPrefix` function with `Contains` for more comprehensive model matching
|
||||
- Added "conceptmap" to VSCode dictionary settings
|
||||
|
||||
### Direct commits
|
||||
|
||||
- Merge branch 'danielmiessler:main' into main
|
||||
- Docs: Fix typo in README
|
||||
|
||||
## v1.4.334 (2025-11-26)
|
||||
|
||||
### PR [#1845](https://github.com/danielmiessler/Fabric/pull/1845) by [ksylvan](https://github.com/ksylvan): Add Claude Opus 4.5 Support
|
||||
|
||||
- Add Claude Opus 4.5 model variants to Anthropic client
|
||||
- Upgrade anthropic-sdk-go from v1.16.0 to v1.19.0
|
||||
- Update golang.org/x/crypto from v0.41.0 to v0.45.0
|
||||
- Upgrade golang.org/x/net from v0.43.0 to v0.47.0
|
||||
- Bump golang.org/x/text from v0.28.0 to v0.31.0
|
||||
|
||||
## v1.4.333 (2025-11-25)
|
||||
|
||||
### PR [#1833](https://github.com/danielmiessler/Fabric/pull/1833) by [junaid18183](https://github.com/junaid18183): Added concall_summary
|
||||
|
||||
- Added concall_summery pattern to extract strategic insights from earnings transcripts for investors.
|
||||
|
||||
### PR [#1844](https://github.com/danielmiessler/Fabric/pull/1844) by [ksylvan](https://github.com/ksylvan): Correct directory name from `concall_summery` to `concall_summary`
|
||||
|
||||
- Fix: correct directory name from `concall_summery` to `concall_summary`
|
||||
- Rename pattern directory to fix spelling error
|
||||
- Update suggest_pattern system with concall_summary references
|
||||
- Add concall_summary to BUSINESS and SUMMARIZE category listings
|
||||
- Add user documentation for earnings call analysis
|
||||
|
||||
## v1.4.332 (2025-11-24)
|
||||
|
||||
### PR [#1843](https://github.com/danielmiessler/Fabric/pull/1843) by [ksylvan](https://github.com/ksylvan): Implement case-insensitive vendor and model name matching
|
||||
|
||||
@@ -73,6 +73,10 @@ Below are the **new features and capabilities** we've added (newest first):
|
||||
|
||||
### Recent Major Features
|
||||
|
||||
- [v1.4.338](https://github.com/danielmiessler/fabric/releases/tag/v1.4.338) (Dec 4, 2025) — Add Abacus vendor support for Chat-LLM
|
||||
models (see [RouteLLM APIs](https://abacus.ai/app/route-llm-apis)).
|
||||
- [v1.4.337](https://github.com/danielmiessler/fabric/releases/tag/v1.4.337) (Dec 4, 2025) — Add "Z AI" vendor support. See the [Z AI overview](https://docs.z.ai/guides/overview/overview) page for more details.
|
||||
- [v1.4.334](https://github.com/danielmiessler/fabric/releases/tag/v1.4.334) (Nov 26, 2025) — **Claude Opus 4.5**: Updates the Anthropic SDK to the latest and adds the new [Claude Opus 4.5](https://www.anthropic.com/news/claude-opus-4-5) to the available models.
|
||||
- [v1.4.331](https://github.com/danielmiessler/fabric/releases/tag/v1.4.331) (Nov 23, 2025) — **Support for GitHub Models**: Adds support for using GitHub Models.
|
||||
- [v1.4.322](https://github.com/danielmiessler/fabric/releases/tag/v1.4.322) (Nov 5, 2025) — **Interactive HTML Concept Maps and Claude Sonnet 4.5**: Adds `create_conceptmap` pattern for visual knowledge representation using Vis.js, introduces WELLNESS category with psychological analysis patterns, and upgrades to Claude Sonnet 4.5
|
||||
- [v1.4.317](https://github.com/danielmiessler/fabric/releases/tag/v1.4.317) (Sep 21, 2025) — **Portuguese Language Variants**: Adds BCP 47 locale normalization with support for Brazilian Portuguese (pt-BR) and European Portuguese (pt-PT) with intelligent fallback chains
|
||||
|
||||
@@ -109,11 +109,11 @@ func ScanDirectory(rootDir string, maxDepth int, instructions string, ignoreList
|
||||
}
|
||||
|
||||
// Create final data structure
|
||||
var data []interface{}
|
||||
var data []any
|
||||
data = append(data, rootItem)
|
||||
|
||||
// Add report
|
||||
reportItem := map[string]interface{}{
|
||||
reportItem := map[string]any{
|
||||
"type": "report",
|
||||
"directories": dirCount,
|
||||
"files": fileCount,
|
||||
@@ -121,7 +121,7 @@ func ScanDirectory(rootDir string, maxDepth int, instructions string, ignoreList
|
||||
data = append(data, reportItem)
|
||||
|
||||
// Add instructions
|
||||
instructionsItem := map[string]interface{}{
|
||||
instructionsItem := map[string]any{
|
||||
"type": "instructions",
|
||||
"name": "code_change_instructions",
|
||||
"details": instructions,
|
||||
|
||||
@@ -12,7 +12,7 @@ import (
|
||||
func main() {
|
||||
err := cli.Cli(version)
|
||||
if err != nil && !flags.WroteHelp(err) {
|
||||
fmt.Printf("%s\n", err)
|
||||
fmt.Fprintf(os.Stderr, "%s\n", err)
|
||||
os.Exit(1)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
package main
|
||||
|
||||
var version = "v1.4.332"
|
||||
var version = "v1.4.349"
|
||||
|
||||
Binary file not shown.
@@ -574,8 +574,8 @@ func (g *Generator) extractChanges(pr *github.PR) []string {
|
||||
}
|
||||
|
||||
if len(changes) == 0 && pr.Body != "" {
|
||||
lines := strings.Split(pr.Body, "\n")
|
||||
for _, line := range lines {
|
||||
lines := strings.SplitSeq(pr.Body, "\n")
|
||||
for line := range lines {
|
||||
line = strings.TrimSpace(line)
|
||||
if strings.HasPrefix(line, "- ") || strings.HasPrefix(line, "* ") {
|
||||
change := strings.TrimPrefix(strings.TrimPrefix(line, "- "), "* ")
|
||||
|
||||
@@ -159,7 +159,7 @@ func (g *Generator) CreateNewChangelogEntry(version string) error {
|
||||
for _, file := range files {
|
||||
// Extract PR number from filename (e.g., "1640.txt" -> 1640)
|
||||
filename := filepath.Base(file)
|
||||
if prNumStr := strings.TrimSuffix(filename, ".txt"); prNumStr != filename {
|
||||
if prNumStr, ok := strings.CutSuffix(filename, ".txt"); ok {
|
||||
if prNum, err := strconv.Atoi(prNumStr); err == nil {
|
||||
processedPRs[prNum] = true
|
||||
prNumbers = append(prNumbers, prNum)
|
||||
|
||||
@@ -333,7 +333,7 @@ func (c *Client) FetchAllMergedPRsGraphQL(since time.Time) ([]*PR, error) {
|
||||
|
||||
for {
|
||||
// Prepare variables
|
||||
variables := map[string]interface{}{
|
||||
variables := map[string]any{
|
||||
"owner": graphql.String(c.owner),
|
||||
"repo": graphql.String(c.repo),
|
||||
"after": (*graphql.String)(after),
|
||||
|
||||
84
data/patterns/concall_summary/system.md
Normal file
84
data/patterns/concall_summary/system.md
Normal file
@@ -0,0 +1,84 @@
|
||||
# IDENTITY and PURPOSE
|
||||
|
||||
You are an equity research analyst specializing in earnings and conference call analysis. Your role involves carefully examining transcripts to extract actionable insights that can inform investment decisions. You need to focus on several key areas, including management commentary, analyst questions, financial and operational insights, risks and red flags, hidden signals, and an executive summary. Your task is to distill complex information into clear, concise bullet points, capturing strategic themes, growth drivers, and potential concerns. It is crucial to interpret the tone, identify contradictions, and highlight any subtle cues that may indicate future strategic shifts or risks.
|
||||
|
||||
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
|
||||
|
||||
# STEPS
|
||||
|
||||
* Analyze the transcript to extract management commentary, focusing on strategic themes, growth drivers, margin commentary, guidance, tone analysis, and any contradictions or vague areas.
|
||||
* Extract a summary of the content in exactly **25 words**, including who is presenting and the content being discussed; place this under a **SUMMARY** section.
|
||||
* For each analyst's question, determine the underlying concern, summarize management’s exact answer, evaluate if the answers address the question fully, and identify anything the management avoided or deflected.
|
||||
* Gather financial and operational insights, including commentary on demand, pricing, capacity, market share, cost inflation, raw material trends, and supply-chain issues.
|
||||
* Identify risks and red flags by noting any negative commentary, early warning signs, unusual wording, delayed responses, repeated disclaimers, and areas where management seemed less confident.
|
||||
* Detect hidden signals such as forward-looking hints, unasked but important questions, and subtle cues about strategy shifts or stress.
|
||||
* Create an executive summary in bullet points, listing the 10 most important takeaways, 3 surprises, and 3 things to track in the next quarter.
|
||||
|
||||
# OUTPUT STRUCTURE
|
||||
|
||||
* MANAGEMENT COMMENTARY
|
||||
|
||||
* Key strategic themes
|
||||
* Growth drivers discussed
|
||||
* Margin commentary
|
||||
* Guidance (explicit + implicit)
|
||||
* Tone analysis (positive/neutral/negative)
|
||||
* Any contradictions or vague areas
|
||||
|
||||
* ANALYST QUESTIONS (Q&A)
|
||||
|
||||
* For each analyst (use bullets, one analyst per bullet-group):
|
||||
|
||||
* Underlying concern (what the question REALLY asked)
|
||||
* Management’s exact answer (concise)
|
||||
* Answer completeness (Yes/No — short explanation)
|
||||
* Items management avoided or deflected
|
||||
|
||||
* FINANCIAL & OPERATIONAL INSIGHTS
|
||||
|
||||
* Demand, pricing, capacity, market share commentary
|
||||
* Cost inflation, raw material trends, supply-chain issues
|
||||
* Segment-wise performance and commentary (if applicable)
|
||||
|
||||
* RISKS & RED FLAGS
|
||||
|
||||
* Negative commentary or early-warning signs
|
||||
* Unusual wording, delayed responses, repeated disclaimers
|
||||
* Areas where management was less confident
|
||||
|
||||
* HIDDEN SIGNALS
|
||||
|
||||
* Forward-looking hints and tone shifts
|
||||
* Important topics not asked by analysts but relevant
|
||||
* Subtle cues of strategy change, stress, or opportunity
|
||||
|
||||
* EXECUTIVE SUMMARY
|
||||
|
||||
* 10 most important takeaways (bullet points)
|
||||
* 3 surprises (bullet points)
|
||||
* 3 things to track next quarter (bullet points)
|
||||
|
||||
* SUMMARY (exactly 25 words)
|
||||
|
||||
* A single 25-word sentence summarizing who presented and what was discussed
|
||||
|
||||
# OUTPUT INSTRUCTIONS
|
||||
|
||||
* Only output Markdown.
|
||||
* Provide everything in clear, crisp bullet points.
|
||||
* Use bulleted lists only; do not use numbered lists.
|
||||
* Begin the output with the **SUMMARY** (exactly 25 words), then the sections in the order shown under **OUTPUT STRUCTURE**.
|
||||
* For **ANALYST QUESTIONS (Q&A)**, keep each analyst’s Q&A grouped and separated by a blank line for readability.
|
||||
* For **EXECUTIVE SUMMARY**, present the 10 takeaways first, then the 3 surprises, then the 3 things to track.
|
||||
* Keep each bullet concise — prefer single-sentence bullets.
|
||||
* Do not include warnings, meta-comments, or process notes in the final output.
|
||||
* Do not repeat ideas, insights, quotes, habits, facts, or references across bullets.
|
||||
* When interpreting tone or identifying a hidden signal, be explicit about the textual clue supporting that interpretation (briefly, within the same bullet).
|
||||
* If any numeric figure or explicit guidance is cited in the transcript, reproduce it verbatim in the relevant bullet and mark it as **(quoted)**.
|
||||
* If information is missing or management declined to answer, state that clearly within the relevant bullet.
|
||||
* Ensure fidelity: do not invent facts not in the transcript. If you infer, label it as an inference.
|
||||
* Ensure you follow ALL these instructions when creating your output.
|
||||
|
||||
# INPUT
|
||||
|
||||
INPUT:
|
||||
@@ -46,188 +46,189 @@
|
||||
42. **clean_text**: Fix broken or malformatted text by correcting line breaks, punctuation, capitalization, and paragraphs without altering content or spelling.
|
||||
43. **coding_master**: Explain a coding concept to a beginner, providing examples, and formatting code in markdown with specific output sections like ideas, recommendations, facts, and insights.
|
||||
44. **compare_and_contrast**: Compare and contrast a list of items in a markdown table, with items on the left and topics on top.
|
||||
45. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
|
||||
46. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
|
||||
47. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
|
||||
48. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
|
||||
49. **create_aphorisms**: Find and generate a list of brief, witty statements.
|
||||
50. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
|
||||
51. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
|
||||
52. **create_coding_feature**: Generates secure and composable code features using modern technology and best practices from project specifications.
|
||||
53. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
|
||||
54. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
|
||||
55. **create_conceptmap**: Transforms unstructured text or markdown content into an interactive HTML concept map using Vis.js by extracting key concepts and their logical relationships.
|
||||
56. **create_cyber_summary**: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
|
||||
57. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
|
||||
58. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
|
||||
59. **create_excalidraw_visualization**: Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
|
||||
60. **create_flash_cards**: Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
|
||||
61. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
|
||||
62. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
|
||||
63. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
|
||||
64. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
|
||||
65. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
|
||||
66. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
|
||||
67. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
|
||||
68. **create_loe_document**: Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
|
||||
69. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
|
||||
70. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
|
||||
71. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
|
||||
72. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
|
||||
73. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
|
||||
74. **create_mnemonic_phrases**: Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
|
||||
75. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
|
||||
76. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
|
||||
77. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
|
||||
78. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
|
||||
79. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
|
||||
80. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
|
||||
81. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
|
||||
82. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
|
||||
83. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
|
||||
84. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
|
||||
85. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
|
||||
86. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
|
||||
87. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
|
||||
88. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
|
||||
89. **create_story_about_people_interaction**: Analyze two personas, compare their dynamics, and craft a realistic, character-driven story from those insights.
|
||||
90. **create_story_about_person**: Creates compelling, realistic short stories based on psychological profiles, showing how characters navigate everyday problems using strategies consistent with their personality traits.
|
||||
91. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
|
||||
92. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
|
||||
93. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
|
||||
94. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
|
||||
95. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
|
||||
96. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
|
||||
97. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
|
||||
98. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
|
||||
99. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
|
||||
100. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
|
||||
101. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
|
||||
102. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
|
||||
103. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
|
||||
104. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
|
||||
105. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
|
||||
106. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
|
||||
107. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
|
||||
108. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
|
||||
109. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
|
||||
110. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
|
||||
111. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
|
||||
112. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
|
||||
113. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
|
||||
114. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
|
||||
115. **extract_characters**: Identify all characters (human and non-human), resolve their aliases and pronouns into canonical names, and produce detailed descriptions of each character's role, motivations, and interactions ranked by narrative importance.
|
||||
116. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
|
||||
117. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
|
||||
118. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
|
||||
119. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
|
||||
120. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
|
||||
121. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
|
||||
122. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
|
||||
123. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
|
||||
124. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
|
||||
125. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
|
||||
126. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
|
||||
127. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
|
||||
128. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
|
||||
129. **extract_mcp_servers**: Identify and summarize Model Context Protocol (MCP) servers referenced in the input along with their key details.
|
||||
130. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
|
||||
131. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
|
||||
132. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
|
||||
133. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
|
||||
134. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
|
||||
135. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
|
||||
136. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
|
||||
137. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
|
||||
138. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
|
||||
139. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
|
||||
140. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
|
||||
141. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
|
||||
142. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
|
||||
143. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
|
||||
144. **extract_videoid**: Extracts and outputs the video ID from any given URL.
|
||||
145. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
|
||||
146. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
|
||||
147. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
|
||||
148. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
|
||||
149. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
|
||||
150. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
|
||||
151. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
|
||||
152. **fix_typos**: Proofreads and corrects typos, spelling, grammar, and punctuation errors in text.
|
||||
153. **generate_code_rules**: Compile best-practice coding rules and guardrails for AI-assisted development workflows from the provided content.
|
||||
154. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
|
||||
155. **heal_person**: Develops a comprehensive plan for spiritual and mental healing based on psychological profiles, providing personalized recommendations for mental health improvement and overall life enhancement.
|
||||
156. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
|
||||
157. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
|
||||
158. **identify_dsrp_perspectives**: Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
|
||||
159. **identify_dsrp_relationships**: Encourages exploration of connections, distinctions, and boundaries between ideas, inspired by systems thinkers to reveal new insights and patterns in complex systems.
|
||||
160. **identify_dsrp_systems**: Encourages organizing ideas into systems of parts and wholes, inspired by systems thinkers to explore relationships and how changes in organization impact meaning and understanding.
|
||||
161. **identify_job_stories**: Identifies key job stories or requirements for roles.
|
||||
162. **improve_academic_writing**: Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
|
||||
163. **improve_prompt**: Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
|
||||
164. **improve_report_finding**: Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
|
||||
165. **improve_writing**: Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning. skills.
|
||||
166. **judge_output**: Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
|
||||
167. **label_and_rate**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
|
||||
168. **md_callout**: Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
|
||||
169. **model_as_sherlock_freud**: Builds psychological models using detective reasoning and psychoanalytic insight to understand human behavior.
|
||||
170. **official_pattern_template**: Template to use if you want to create new fabric patterns.
|
||||
171. **predict_person_actions**: Predicts behavioral responses based on psychological profiles and challenges.
|
||||
172. **prepare_7s_strategy**: Prepares a comprehensive briefing document from 7S's strategy capturing organizational profile, strategic elements, and market dynamics with clear, concise, and organized content.
|
||||
173. **provide_guidance**: Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
|
||||
174. **rate_ai_response**: Rates the quality of AI responses by comparing them to top human expert performance, assigning a letter grade, reasoning, and providing a 1-100 score based on the evaluation.
|
||||
175. **rate_ai_result**: Assesses the quality of AI/ML/LLM work by deeply analyzing content, instructions, and output, then rates performance based on multiple dimensions, including coverage, creativity, and interdisciplinary thinking.
|
||||
176. **rate_content**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
|
||||
177. **rate_value**: Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
|
||||
178. **raw_query**: Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
|
||||
179. **recommend_artists**: Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
|
||||
180. **recommend_pipeline_upgrades**: Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
|
||||
181. **recommend_talkpanel_topics**: Produces a clean set of proposed talks or panel talking points for a person based on their interests and goals, formatted for submission to a conference organizer.
|
||||
182. **recommend_yoga_practice**: Provides personalized yoga sequences, meditation guidance, and holistic lifestyle advice based on individual profiles.
|
||||
183. **refine_design_document**: Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
|
||||
184. **review_design**: Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
|
||||
185. **sanitize_broken_html_to_markdown**: Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
|
||||
186. **suggest_pattern**: Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
|
||||
187. **summarize**: Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
|
||||
188. **summarize_board_meeting**: Creates formal meeting notes from board meeting transcripts for corporate governance documentation.
|
||||
189. **summarize_debate**: Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
|
||||
190. **summarize_git_changes**: Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
|
||||
191. **summarize_git_diff**: Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
|
||||
192. **summarize_lecture**: Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
|
||||
193. **summarize_legislation**: Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
|
||||
194. **summarize_meeting**: Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
|
||||
195. **summarize_micro**: Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
|
||||
196. **summarize_newsletter**: Extracts the most meaningful, interesting, and useful content from a newsletter, summarizing key sections such as content, opinions, tools, companies, and follow-up items in clear, structured Markdown.
|
||||
197. **summarize_paper**: Summarizes an academic paper by detailing its title, authors, technical approach, distinctive features, experimental setup, results, advantages, limitations, and conclusion in a clear, structured format using human-readable Markdown.
|
||||
198. **summarize_prompt**: Summarizes AI chat prompts by describing the primary function, unique approach, and expected output in a concise paragraph. The summary is focused on the prompt's purpose without unnecessary details or formatting.
|
||||
199. **summarize_pull-requests**: Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
|
||||
200. **summarize_rpg_session**: Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
|
||||
201. **t_analyze_challenge_handling**: Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
|
||||
202. **t_check_dunning_kruger**: Assess narratives for Dunning-Kruger patterns by contrasting self-perception with demonstrated competence and confidence cues.
|
||||
203. **t_check_metrics**: Analyzes deep context from the TELOS file and input instruction, then provides a wisdom-based output while considering metrics and KPIs to assess recent improvements.
|
||||
204. **t_create_h3_career**: Summarizes context and produces wisdom-based output by deeply analyzing both the TELOS File and the input instruction, considering the relationship between the two.
|
||||
205. **t_create_opening_sentences**: Describes from TELOS file the person's identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
|
||||
206. **t_describe_life_outlook**: Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
|
||||
207. **t_extract_intro_sentences**: Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
|
||||
208. **t_extract_panel_topics**: Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
|
||||
209. **t_find_blindspots**: Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
|
||||
210. **t_find_negative_thinking**: Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
|
||||
211. **t_find_neglected_goals**: Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
|
||||
212. **t_give_encouragement**: Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
|
||||
213. **t_red_team_thinking**: Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
|
||||
214. **t_threat_model_plans**: Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
|
||||
215. **t_visualize_mission_goals_projects**: Analyze a TELOS file and input instructions to create an ASCII art diagram illustrating the relationship of missions, goals, and projects.
|
||||
216. **t_year_in_review**: Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
|
||||
217. **to_flashcards**: Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
|
||||
218. **transcribe_minutes**: Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
|
||||
219. **translate**: Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
|
||||
220. **tweet**: Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
|
||||
221. **write_essay**: Writes essays in the style of a specified author, embodying their unique voice, vocabulary, and approach. Uses `author_name` variable.
|
||||
222. **write_essay_pg**: Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
|
||||
223. **write_hackerone_report**: Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
|
||||
224. **write_latex**: Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
|
||||
225. **write_micro_essay**: Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
|
||||
226. **write_nuclei_template_rule**: Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
|
||||
227. **write_pull-request**: Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
|
||||
228. **write_semgrep_rule**: Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
|
||||
229. **youtube_summary**: Create concise, timestamped Youtube video summaries that highlight key points.
|
||||
45. **concall_summary**: Analyzes earnings and conference call transcripts to extract management commentary, analyst Q&A, financial insights, risks, and executive summaries.
|
||||
46. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
|
||||
47. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
|
||||
48. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
|
||||
49. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
|
||||
50. **create_aphorisms**: Find and generate a list of brief, witty statements.
|
||||
51. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
|
||||
52. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
|
||||
53. **create_coding_feature**: Generates secure and composable code features using modern technology and best practices from project specifications.
|
||||
54. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
|
||||
55. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
|
||||
56. **create_conceptmap**: Transforms unstructured text or markdown content into an interactive HTML concept map using Vis.js by extracting key concepts and their logical relationships.
|
||||
57. **create_cyber_summary**: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
|
||||
58. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
|
||||
59. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
|
||||
60. **create_excalidraw_visualization**: Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
|
||||
61. **create_flash_cards**: Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
|
||||
62. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
|
||||
63. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
|
||||
64. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
|
||||
65. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
|
||||
66. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
|
||||
67. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
|
||||
68. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
|
||||
69. **create_loe_document**: Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
|
||||
70. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
|
||||
71. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
|
||||
72. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
|
||||
73. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
|
||||
74. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
|
||||
75. **create_mnemonic_phrases**: Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
|
||||
76. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
|
||||
77. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
|
||||
78. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
|
||||
79. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
|
||||
80. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
|
||||
81. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
|
||||
82. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
|
||||
83. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
|
||||
84. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
|
||||
85. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
|
||||
86. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
|
||||
87. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
|
||||
88. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
|
||||
89. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
|
||||
90. **create_story_about_people_interaction**: Analyze two personas, compare their dynamics, and craft a realistic, character-driven story from those insights.
|
||||
91. **create_story_about_person**: Creates compelling, realistic short stories based on psychological profiles, showing how characters navigate everyday problems using strategies consistent with their personality traits.
|
||||
92. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
|
||||
93. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
|
||||
94. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
|
||||
95. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
|
||||
96. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
|
||||
97. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
|
||||
98. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
|
||||
99. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
|
||||
100. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
|
||||
101. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
|
||||
102. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
|
||||
103. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
|
||||
104. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
|
||||
105. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
|
||||
106. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
|
||||
107. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
|
||||
108. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
|
||||
109. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
|
||||
110. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
|
||||
111. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
|
||||
112. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
|
||||
113. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
|
||||
114. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
|
||||
115. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
|
||||
116. **extract_characters**: Identify all characters (human and non-human), resolve their aliases and pronouns into canonical names, and produce detailed descriptions of each character's role, motivations, and interactions ranked by narrative importance.
|
||||
117. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
|
||||
118. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
|
||||
119. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
|
||||
120. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
|
||||
121. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
|
||||
122. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
|
||||
123. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
|
||||
124. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
|
||||
125. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
|
||||
126. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
|
||||
127. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
|
||||
128. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
|
||||
129. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
|
||||
130. **extract_mcp_servers**: Identify and summarize Model Context Protocol (MCP) servers referenced in the input along with their key details.
|
||||
131. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
|
||||
132. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
|
||||
133. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
|
||||
134. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
|
||||
135. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
|
||||
136. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
|
||||
137. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
|
||||
138. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
|
||||
139. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
|
||||
140. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
|
||||
141. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
|
||||
142. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
|
||||
143. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
|
||||
144. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
|
||||
145. **extract_videoid**: Extracts and outputs the video ID from any given URL.
|
||||
146. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
|
||||
147. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
|
||||
148. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
|
||||
149. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
|
||||
150. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
|
||||
151. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
|
||||
152. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
|
||||
153. **fix_typos**: Proofreads and corrects typos, spelling, grammar, and punctuation errors in text.
|
||||
154. **generate_code_rules**: Compile best-practice coding rules and guardrails for AI-assisted development workflows from the provided content.
|
||||
155. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
|
||||
156. **heal_person**: Develops a comprehensive plan for spiritual and mental healing based on psychological profiles, providing personalized recommendations for mental health improvement and overall life enhancement.
|
||||
157. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
|
||||
158. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
|
||||
159. **identify_dsrp_perspectives**: Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
|
||||
160. **identify_dsrp_relationships**: Encourages exploration of connections, distinctions, and boundaries between ideas, inspired by systems thinkers to reveal new insights and patterns in complex systems.
|
||||
161. **identify_dsrp_systems**: Encourages organizing ideas into systems of parts and wholes, inspired by systems thinkers to explore relationships and how changes in organization impact meaning and understanding.
|
||||
162. **identify_job_stories**: Identifies key job stories or requirements for roles.
|
||||
163. **improve_academic_writing**: Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
|
||||
164. **improve_prompt**: Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
|
||||
165. **improve_report_finding**: Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
|
||||
166. **improve_writing**: Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning. skills.
|
||||
167. **judge_output**: Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
|
||||
168. **label_and_rate**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
|
||||
169. **md_callout**: Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
|
||||
170. **model_as_sherlock_freud**: Builds psychological models using detective reasoning and psychoanalytic insight to understand human behavior.
|
||||
171. **official_pattern_template**: Template to use if you want to create new fabric patterns.
|
||||
172. **predict_person_actions**: Predicts behavioral responses based on psychological profiles and challenges.
|
||||
173. **prepare_7s_strategy**: Prepares a comprehensive briefing document from 7S's strategy capturing organizational profile, strategic elements, and market dynamics with clear, concise, and organized content.
|
||||
174. **provide_guidance**: Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
|
||||
175. **rate_ai_response**: Rates the quality of AI responses by comparing them to top human expert performance, assigning a letter grade, reasoning, and providing a 1-100 score based on the evaluation.
|
||||
176. **rate_ai_result**: Assesses the quality of AI/ML/LLM work by deeply analyzing content, instructions, and output, then rates performance based on multiple dimensions, including coverage, creativity, and interdisciplinary thinking.
|
||||
177. **rate_content**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
|
||||
178. **rate_value**: Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
|
||||
179. **raw_query**: Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
|
||||
180. **recommend_artists**: Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
|
||||
181. **recommend_pipeline_upgrades**: Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
|
||||
182. **recommend_talkpanel_topics**: Produces a clean set of proposed talks or panel talking points for a person based on their interests and goals, formatted for submission to a conference organizer.
|
||||
183. **recommend_yoga_practice**: Provides personalized yoga sequences, meditation guidance, and holistic lifestyle advice based on individual profiles.
|
||||
184. **refine_design_document**: Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
|
||||
185. **review_design**: Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
|
||||
186. **sanitize_broken_html_to_markdown**: Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
|
||||
187. **suggest_pattern**: Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
|
||||
188. **summarize**: Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
|
||||
189. **summarize_board_meeting**: Creates formal meeting notes from board meeting transcripts for corporate governance documentation.
|
||||
190. **summarize_debate**: Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
|
||||
191. **summarize_git_changes**: Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
|
||||
192. **summarize_git_diff**: Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
|
||||
193. **summarize_lecture**: Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
|
||||
194. **summarize_legislation**: Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
|
||||
195. **summarize_meeting**: Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
|
||||
196. **summarize_micro**: Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
|
||||
197. **summarize_newsletter**: Extracts the most meaningful, interesting, and useful content from a newsletter, summarizing key sections such as content, opinions, tools, companies, and follow-up items in clear, structured Markdown.
|
||||
198. **summarize_paper**: Summarizes an academic paper by detailing its title, authors, technical approach, distinctive features, experimental setup, results, advantages, limitations, and conclusion in a clear, structured format using human-readable Markdown.
|
||||
199. **summarize_prompt**: Summarizes AI chat prompts by describing the primary function, unique approach, and expected output in a concise paragraph. The summary is focused on the prompt's purpose without unnecessary details or formatting.
|
||||
200. **summarize_pull-requests**: Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
|
||||
201. **summarize_rpg_session**: Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
|
||||
202. **t_analyze_challenge_handling**: Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
|
||||
203. **t_check_dunning_kruger**: Assess narratives for Dunning-Kruger patterns by contrasting self-perception with demonstrated competence and confidence cues.
|
||||
204. **t_check_metrics**: Analyzes deep context from the TELOS file and input instruction, then provides a wisdom-based output while considering metrics and KPIs to assess recent improvements.
|
||||
205. **t_create_h3_career**: Summarizes context and produces wisdom-based output by deeply analyzing both the TELOS File and the input instruction, considering the relationship between the two.
|
||||
206. **t_create_opening_sentences**: Describes from TELOS file the person's identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
|
||||
207. **t_describe_life_outlook**: Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
|
||||
208. **t_extract_intro_sentences**: Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
|
||||
209. **t_extract_panel_topics**: Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
|
||||
210. **t_find_blindspots**: Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
|
||||
211. **t_find_negative_thinking**: Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
|
||||
212. **t_find_neglected_goals**: Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
|
||||
213. **t_give_encouragement**: Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
|
||||
214. **t_red_team_thinking**: Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
|
||||
215. **t_threat_model_plans**: Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
|
||||
216. **t_visualize_mission_goals_projects**: Analyze a TELOS file and input instructions to create an ASCII art diagram illustrating the relationship of missions, goals, and projects.
|
||||
217. **t_year_in_review**: Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
|
||||
218. **to_flashcards**: Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
|
||||
219. **transcribe_minutes**: Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
|
||||
220. **translate**: Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
|
||||
221. **tweet**: Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
|
||||
222. **write_essay**: Writes essays in the style of a specified author, embodying their unique voice, vocabulary, and approach. Uses `author_name` variable.
|
||||
223. **write_essay_pg**: Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
|
||||
224. **write_hackerone_report**: Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
|
||||
225. **write_latex**: Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
|
||||
226. **write_micro_essay**: Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
|
||||
227. **write_nuclei_template_rule**: Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
|
||||
228. **write_pull-request**: Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
|
||||
229. **write_semgrep_rule**: Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
|
||||
230. **youtube_summary**: Create concise, timestamped Youtube video summaries that highlight key points.
|
||||
|
||||
@@ -73,11 +73,11 @@ Match the request to one or more of these primary categories:
|
||||
|
||||
**AI**: ai, create_ai_jobs_analysis, create_art_prompt, create_pattern, create_prediction_block, extract_mcp_servers, extract_wisdom_agents, generate_code_rules, improve_prompt, judge_output, rate_ai_response, rate_ai_result, raw_query, suggest_pattern, summarize_prompt
|
||||
|
||||
**ANALYSIS**: ai, analyze_answers, analyze_bill, analyze_bill_short, analyze_candidates, analyze_cfp_submission, analyze_claims, analyze_comments, analyze_debate, analyze_email_headers, analyze_incident, analyze_interviewer_techniques, analyze_logs, analyze_malware, analyze_military_strategy, analyze_mistakes, analyze_paper, analyze_paper_simple, analyze_patent, analyze_personality, analyze_presentation, analyze_product_feedback, analyze_proposition, analyze_prose, analyze_prose_json, analyze_prose_pinker, analyze_risk, analyze_sales_call, analyze_spiritual_text, analyze_tech_impact, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, apply_ul_tags, check_agreement, compare_and_contrast, create_ai_jobs_analysis, create_idea_compass, create_investigation_visualization, create_prediction_block, create_recursive_outline, create_story_about_people_interaction, create_tags, dialog_with_socrates, extract_main_idea, extract_predictions, find_hidden_message, find_logical_fallacies, get_wow_per_minute, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, identify_job_stories, label_and_rate, model_as_sherlock_freud, predict_person_actions, prepare_7s_strategy, provide_guidance, rate_content, rate_value, recommend_artists, recommend_talkpanel_topics, review_design, summarize_board_meeting, t_analyze_challenge_handling, t_check_dunning_kruger, t_check_metrics, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_find_blindspots, t_find_negative_thinking, t_red_team_thinking, t_threat_model_plans, t_year_in_review, write_hackerone_report
|
||||
**ANALYSIS**: ai, analyze_answers, analyze_bill, analyze_bill_short, analyze_candidates, analyze_cfp_submission, analyze_claims, analyze_comments, analyze_debate, analyze_email_headers, analyze_incident, analyze_interviewer_techniques, analyze_logs, analyze_malware, analyze_military_strategy, analyze_mistakes, analyze_paper, analyze_paper_simple, analyze_patent, analyze_personality, analyze_presentation, analyze_product_feedback, analyze_proposition, analyze_prose, analyze_prose_json, analyze_prose_pinker, analyze_risk, analyze_sales_call, analyze_spiritual_text, analyze_tech_impact, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, apply_ul_tags, check_agreement, compare_and_contrast, concall_summary, create_ai_jobs_analysis, create_idea_compass, create_investigation_visualization, create_prediction_block, create_recursive_outline, create_story_about_people_interaction, create_tags, dialog_with_socrates, extract_main_idea, extract_predictions, find_hidden_message, find_logical_fallacies, get_wow_per_minute, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, identify_job_stories, label_and_rate, model_as_sherlock_freud, predict_person_actions, prepare_7s_strategy, provide_guidance, rate_content, rate_value, recommend_artists, recommend_talkpanel_topics, review_design, summarize_board_meeting, t_analyze_challenge_handling, t_check_dunning_kruger, t_check_metrics, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_find_blindspots, t_find_negative_thinking, t_red_team_thinking, t_threat_model_plans, t_year_in_review, write_hackerone_report
|
||||
|
||||
**BILL**: analyze_bill, analyze_bill_short
|
||||
|
||||
**BUSINESS**: check_agreement, create_ai_jobs_analysis, create_formal_email, create_hormozi_offer, create_loe_document, create_logo, create_newsletter_entry, create_prd, explain_project, extract_business_ideas, extract_characters, extract_product_features, extract_skills, extract_sponsors, identify_job_stories, prepare_7s_strategy, rate_value, t_check_metrics, t_create_h3_career, t_visualize_mission_goals_projects, t_year_in_review, transcribe_minutes
|
||||
**BUSINESS**: check_agreement, concall_summary, create_ai_jobs_analysis, create_formal_email, create_hormozi_offer, create_loe_document, create_logo, create_newsletter_entry, create_prd, explain_project, extract_business_ideas, extract_characters, extract_product_features, extract_skills, extract_sponsors, identify_job_stories, prepare_7s_strategy, rate_value, t_check_metrics, t_create_h3_career, t_visualize_mission_goals_projects, t_year_in_review, transcribe_minutes
|
||||
|
||||
**CLASSIFICATION**: apply_ul_tags
|
||||
|
||||
@@ -109,7 +109,7 @@ Match the request to one or more of these primary categories:
|
||||
|
||||
**STRATEGY**: analyze_military_strategy, create_better_frame, prepare_7s_strategy, t_analyze_challenge_handling, t_find_blindspots, t_find_negative_thinking, t_find_neglected_goals, t_red_team_thinking, t_threat_model_plans, t_visualize_mission_goals_projects
|
||||
|
||||
**SUMMARIZE**: capture_thinkers_work, create_5_sentence_summary, create_micro_summary, create_newsletter_entry, create_show_intro, create_summary, extract_core_message, extract_latest_video, extract_main_idea, summarize, summarize_board_meeting, summarize_debate, summarize_git_changes, summarize_git_diff, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_pull-requests, summarize_rpg_session, youtube_summary
|
||||
**SUMMARIZE**: capture_thinkers_work, concall_summary, create_5_sentence_summary, create_micro_summary, create_newsletter_entry, create_show_intro, create_summary, extract_core_message, extract_latest_video, extract_main_idea, summarize, summarize_board_meeting, summarize_debate, summarize_git_changes, summarize_git_diff, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_pull-requests, summarize_rpg_session, youtube_summary
|
||||
|
||||
**VISUALIZE**: create_conceptmap, create_excalidraw_visualization, create_graph_from_input, create_idea_compass, create_investigation_visualization, create_keynote, create_logo, create_markmap_visualization, create_mermaid_visualization, create_mermaid_visualization_for_github, create_video_chapters, create_visualization, enrich_blog_post, t_visualize_mission_goals_projects
|
||||
|
||||
|
||||
@@ -196,6 +196,10 @@ Review contract to identify stipulations, issues, and changes for negotiation.
|
||||
|
||||
Create comparisons table, highlighting key differences and similarities.
|
||||
|
||||
### concall_summary
|
||||
|
||||
Analyze earnings call transcripts to extract management insights, financial metrics, and investment implications.
|
||||
|
||||
### create_ai_jobs_analysis
|
||||
|
||||
Identify automation risks and career resilience strategies.
|
||||
|
||||
@@ -51,6 +51,29 @@ docs: update installation instructions
|
||||
|
||||
## Pull Request Process
|
||||
|
||||
### Pull Request Guidelines
|
||||
|
||||
**Keep pull requests focused and minimal.**
|
||||
|
||||
PRs that touch a large number of files (50+) without clear functional justification will likely be rejected without detailed review.
|
||||
|
||||
#### Why we enforce this
|
||||
|
||||
- **Reviewability**: Large PRs are effectively un-reviewable. Studies show reviewer effectiveness drops significantly after ~200-400 lines of code. A 93-file "cleanup" PR cannot receive meaningful review.
|
||||
- **Git history**: Sweeping changes pollute `git blame`, making it harder to trace when and why functional changes were made.
|
||||
- **Merge conflicts**: Large PRs increase the likelihood of conflicts with other contributors' work.
|
||||
- **Risk**: More changed lines means more opportunities for subtle bugs, even in "safe" refactors.
|
||||
|
||||
#### What to do instead
|
||||
|
||||
If you have a large change in mind, break it into logical, independently-mergeable slices. For example:
|
||||
|
||||
- ✅ "Replace `interface{}` with `any` across codebase" (single mechanical change, easy to verify)
|
||||
- ✅ "Migrate to `strings.CutPrefix` in `internal/cli`" (scoped to one package)
|
||||
- ❌ "Modernize codebase with multiple idiom updates" (too broad, impossible to review)
|
||||
|
||||
For sweeping refactors or style changes, **open an issue first** to discuss the approach with maintainers before investing time in the work.
|
||||
|
||||
### Changelog Generation (REQUIRED)
|
||||
|
||||
After opening your PR, generate a changelog entry:
|
||||
|
||||
24
flake.lock
generated
24
flake.lock
generated
@@ -5,11 +5,11 @@
|
||||
"systems": "systems"
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1694529238,
|
||||
"narHash": "sha256-zsNZZGTGnMOf9YpHKJqMSsa0dXbfmxeoJ7xHlrt+xmY=",
|
||||
"lastModified": 1731533236,
|
||||
"narHash": "sha256-l0KFg5HjrsfsO/JpG+r7fRrqm12kzFHyUHqHCVpMMbI=",
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "ff7b65b44d01cf9ba6a71320833626af21126384",
|
||||
"rev": "11707dc2f618dd54ca8739b309ec4fc024de578b",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
@@ -26,11 +26,11 @@
|
||||
]
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1742209644,
|
||||
"narHash": "sha256-jMy1XqXqD0/tJprEbUmKilTkvbDY/C0ZGSsJJH4TNCE=",
|
||||
"lastModified": 1763982521,
|
||||
"narHash": "sha256-ur4QIAHwgFc0vXiaxn5No/FuZicxBr2p0gmT54xZkUQ=",
|
||||
"owner": "nix-community",
|
||||
"repo": "gomod2nix",
|
||||
"rev": "8f3534eb8f6c5c3fce799376dc3b91bae6b11884",
|
||||
"rev": "02e63a239d6eabd595db56852535992c898eba72",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
@@ -41,11 +41,11 @@
|
||||
},
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1745234285,
|
||||
"narHash": "sha256-GfpyMzxwkfgRVN0cTGQSkTC0OHhEkv3Jf6Tcjm//qZ0=",
|
||||
"lastModified": 1765472234,
|
||||
"narHash": "sha256-9VvC20PJPsleGMewwcWYKGzDIyjckEz8uWmT0vCDYK0=",
|
||||
"owner": "nixos",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "c11863f1e964833214b767f4a369c6e6a7aba141",
|
||||
"rev": "2fbfb1d73d239d2402a8fe03963e37aab15abe8b",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
@@ -100,11 +100,11 @@
|
||||
]
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1744961264,
|
||||
"narHash": "sha256-aRmUh0AMwcbdjJHnytg1e5h5ECcaWtIFQa6d9gI85AI=",
|
||||
"lastModified": 1762938485,
|
||||
"narHash": "sha256-AlEObg0syDl+Spi4LsZIBrjw+snSVU4T8MOeuZJUJjM=",
|
||||
"owner": "numtide",
|
||||
"repo": "treefmt-nix",
|
||||
"rev": "8d404a69efe76146368885110f29a2ca3700bee6",
|
||||
"rev": "5b4ee75aeefd1e2d5a1cc43cf6ba65eba75e83e4",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
||||
12
go.mod
12
go.mod
@@ -3,7 +3,7 @@ module github.com/danielmiessler/fabric
|
||||
go 1.25.1
|
||||
|
||||
require (
|
||||
github.com/anthropics/anthropic-sdk-go v1.16.0
|
||||
github.com/anthropics/anthropic-sdk-go v1.19.0
|
||||
github.com/atotto/clipboard v0.1.4
|
||||
github.com/aws/aws-sdk-go-v2 v1.39.0
|
||||
github.com/aws/aws-sdk-go-v2/config v1.31.8
|
||||
@@ -29,7 +29,7 @@ require (
|
||||
github.com/spf13/cobra v1.9.1
|
||||
github.com/stretchr/testify v1.11.1
|
||||
golang.org/x/oauth2 v0.30.0
|
||||
golang.org/x/text v0.28.0
|
||||
golang.org/x/text v0.31.0
|
||||
google.golang.org/api v0.247.0
|
||||
gopkg.in/yaml.v3 v3.0.1
|
||||
)
|
||||
@@ -118,11 +118,11 @@ require (
|
||||
go.opentelemetry.io/otel/metric v1.36.0 // indirect
|
||||
go.opentelemetry.io/otel/trace v1.36.0 // indirect
|
||||
golang.org/x/arch v0.18.0 // indirect
|
||||
golang.org/x/crypto v0.41.0 // indirect
|
||||
golang.org/x/crypto v0.45.0 // indirect
|
||||
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b // indirect
|
||||
golang.org/x/net v0.43.0 // indirect
|
||||
golang.org/x/sync v0.16.0 // indirect
|
||||
golang.org/x/sys v0.35.0 // indirect
|
||||
golang.org/x/net v0.47.0 // indirect
|
||||
golang.org/x/sync v0.18.0 // indirect
|
||||
golang.org/x/sys v0.38.0 // indirect
|
||||
google.golang.org/genai v1.17.0
|
||||
google.golang.org/genproto/googleapis/api v0.0.0-20250818200422-3122310a409c // indirect
|
||||
google.golang.org/genproto/googleapis/rpc v0.0.0-20250818200422-3122310a409c // indirect
|
||||
|
||||
13
go.sum
13
go.sum
@@ -29,6 +29,8 @@ github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be h1:9AeTilPcZAjCFI
|
||||
github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be/go.mod h1:ySMOLuWl6zY27l47sB3qLNK6tF2fkHG55UZxx8oIVo4=
|
||||
github.com/anthropics/anthropic-sdk-go v1.16.0 h1:nRkOFDqYXsHteoIhjdJr/5dsiKbFF3rflSv8ax50y8o=
|
||||
github.com/anthropics/anthropic-sdk-go v1.16.0/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
|
||||
github.com/anthropics/anthropic-sdk-go v1.19.0 h1:mO6E+ffSzLRvR/YUH9KJC0uGw0uV8GjISIuzem//3KE=
|
||||
github.com/anthropics/anthropic-sdk-go v1.19.0/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
|
||||
github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de h1:FxWPpzIjnTlhPwqqXc4/vE0f7GvRjuAsbW+HOIe8KnA=
|
||||
github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de/go.mod h1:DCaWoUhZrYW9p1lxo/cm8EmUOOzAPSEZNGF2DK1dJgw=
|
||||
github.com/armon/go-socks5 v0.0.0-20160902184237-e75332964ef5 h1:0CwZNZbxp69SHPdPJAN/hZIm0C4OItdklCFmMRWYpio=
|
||||
@@ -290,6 +292,8 @@ golang.org/x/crypto v0.23.0/go.mod h1:CKFgDieR+mRhux2Lsu27y0fO304Db0wZe70UKqHu0v
|
||||
golang.org/x/crypto v0.31.0/go.mod h1:kDsLvtWBEx7MV9tJOj9bnXsPbxwJQ6csT/x4KIN4Ssk=
|
||||
golang.org/x/crypto v0.41.0 h1:WKYxWedPGCTVVl5+WHSSrOBT0O8lx32+zxmHxijgXp4=
|
||||
golang.org/x/crypto v0.41.0/go.mod h1:pO5AFd7FA68rFak7rOAGVuygIISepHftHnr8dr6+sUc=
|
||||
golang.org/x/crypto v0.45.0 h1:jMBrvKuj23MTlT0bQEOBcAE0mjg8mK9RXFhRH6nyF3Q=
|
||||
golang.org/x/crypto v0.45.0/go.mod h1:XTGrrkGJve7CYK7J8PEww4aY7gM3qMCElcJQ8n8JdX4=
|
||||
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b h1:QoALfVG9rhQ/M7vYDScfPdWjGL9dlsVVM5VGh7aKoAA=
|
||||
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b/go.mod h1:U6Lno4MTRCDY+Ba7aCcauB9T60gsv5s4ralQzP72ZoQ=
|
||||
golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
|
||||
@@ -309,6 +313,8 @@ golang.org/x/net v0.25.0/go.mod h1:JkAGAh7GEvH74S6FOH42FLoXpXbE/aqXSrIQjXgsiwM=
|
||||
golang.org/x/net v0.33.0/go.mod h1:HXLR5J+9DxmrqMwG9qjGCxZ+zKXxBru04zlTvWlWuN4=
|
||||
golang.org/x/net v0.43.0 h1:lat02VYK2j4aLzMzecihNvTlJNQUq316m2Mr9rnM6YE=
|
||||
golang.org/x/net v0.43.0/go.mod h1:vhO1fvI4dGsIjh73sWfUVjj3N7CA9WkKJNQm2svM6Jg=
|
||||
golang.org/x/net v0.47.0 h1:Mx+4dIFzqraBXUugkia1OOvlD6LemFo1ALMHjrXDOhY=
|
||||
golang.org/x/net v0.47.0/go.mod h1:/jNxtkgq5yWUGYkaZGqo27cfGZ1c5Nen03aYrrKpVRU=
|
||||
golang.org/x/oauth2 v0.30.0 h1:dnDm7JmhM45NNpd8FDDeLhK6FwqbOf4MLCM9zb1BOHI=
|
||||
golang.org/x/oauth2 v0.30.0/go.mod h1:B++QgG3ZKulg6sRPGD/mqlHQs5rB3Ml9erfeDY7xKlU=
|
||||
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
@@ -320,6 +326,8 @@ golang.org/x/sync v0.7.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/sync v0.16.0 h1:ycBJEhp9p4vXvUZNszeOq0kGTPghopOL8q0fq3vstxw=
|
||||
golang.org/x/sync v0.16.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
|
||||
golang.org/x/sync v0.18.0 h1:kr88TuHDroi+UVf+0hZnirlk8o8T+4MrK6mr60WkH/I=
|
||||
golang.org/x/sync v0.18.0/go.mod h1:9KTHXmSnoGruLpwFjVSX0lNNA75CykiMECbovNTZqGI=
|
||||
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
|
||||
golang.org/x/sys v0.0.0-20191026070338-33540a1f6037/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
@@ -338,6 +346,8 @@ golang.org/x/sys v0.20.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
|
||||
golang.org/x/sys v0.28.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
|
||||
golang.org/x/sys v0.35.0 h1:vz1N37gP5bs89s7He8XuIYXpyY0+QlsKmzipCbUtyxI=
|
||||
golang.org/x/sys v0.35.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
|
||||
golang.org/x/sys v0.38.0 h1:3yZWxaJjBmCWXqhN1qh02AkOnCQ1poK6oF+a7xWL6Gc=
|
||||
golang.org/x/sys v0.38.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
|
||||
golang.org/x/telemetry v0.0.0-20240228155512-f48c80bd79b2/go.mod h1:TeRTkGYfJXctD9OcfyVLyj2J3IxLnKwHJR8f4D8a3YE=
|
||||
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
|
||||
golang.org/x/term v0.0.0-20210927222741-03fcf44c2211/go.mod h1:jbD1KX2456YbFQfuXm/mYQcufACuNUgVhRMnK/tPxf8=
|
||||
@@ -349,6 +359,7 @@ golang.org/x/term v0.20.0/go.mod h1:8UkIAJTvZgivsXaD6/pH6U9ecQzZ45awqEOzuCvwpFY=
|
||||
golang.org/x/term v0.27.0/go.mod h1:iMsnZpn0cago0GOrHO2+Y7u7JPn5AylBrcoWkElMTSM=
|
||||
golang.org/x/term v0.34.0 h1:O/2T7POpk0ZZ7MAzMeWFSg6S5IpWd/RXDlM9hgM3DR4=
|
||||
golang.org/x/term v0.34.0/go.mod h1:5jC53AEywhIVebHgPVeg0mj8OD3VO9OzclacVrqpaAw=
|
||||
golang.org/x/term v0.37.0 h1:8EGAD0qCmHYZg6J17DvsMy9/wJ7/D/4pV/wfnld5lTU=
|
||||
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
|
||||
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
|
||||
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
|
||||
@@ -361,6 +372,8 @@ golang.org/x/text v0.15.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
|
||||
golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
|
||||
golang.org/x/text v0.28.0 h1:rhazDwis8INMIwQ4tpjLDzUhx6RlXqZNPEM0huQojng=
|
||||
golang.org/x/text v0.28.0/go.mod h1:U8nCwOR8jO/marOQ0QbDiOngZVEBB7MAiitBuMjXiNU=
|
||||
golang.org/x/text v0.31.0 h1:aC8ghyu4JhP8VojJ2lEHBnochRno1sgL6nEi9WGFGMM=
|
||||
golang.org/x/text v0.31.0/go.mod h1:tKRAlv61yKIjGGHX/4tP1LTbc13YSec1pxVEWXzfoeM=
|
||||
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
|
||||
golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
|
||||
golang.org/x/tools v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
|
||||
|
||||
@@ -8,6 +8,7 @@ import (
|
||||
"os"
|
||||
"path/filepath"
|
||||
"reflect"
|
||||
"slices"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
@@ -115,7 +116,7 @@ func Init() (ret *Flags, err error) {
|
||||
|
||||
// Create mapping from flag names (both short and long) to yaml tag names
|
||||
flagToYamlTag := make(map[string]string)
|
||||
t := reflect.TypeOf(Flags{})
|
||||
t := reflect.TypeFor[Flags]()
|
||||
for i := 0; i < t.NumField(); i++ {
|
||||
field := t.Field(i)
|
||||
yamlTag := field.Tag.Get("yaml")
|
||||
@@ -224,14 +225,14 @@ func Init() (ret *Flags, err error) {
|
||||
}
|
||||
|
||||
func parseDebugLevel(args []string) int {
|
||||
for i := 0; i < len(args); i++ {
|
||||
for i := range args {
|
||||
arg := args[i]
|
||||
if arg == "--debug" && i+1 < len(args) {
|
||||
if lvl, err := strconv.Atoi(args[i+1]); err == nil {
|
||||
return lvl
|
||||
}
|
||||
} else if strings.HasPrefix(arg, "--debug=") {
|
||||
if lvl, err := strconv.Atoi(strings.TrimPrefix(arg, "--debug=")); err == nil {
|
||||
} else if after, ok := strings.CutPrefix(arg, "--debug="); ok {
|
||||
if lvl, err := strconv.Atoi(after); err == nil {
|
||||
return lvl
|
||||
}
|
||||
}
|
||||
@@ -241,8 +242,8 @@ func parseDebugLevel(args []string) int {
|
||||
|
||||
func extractFlag(arg string) string {
|
||||
var flag string
|
||||
if strings.HasPrefix(arg, "--") {
|
||||
flag = strings.TrimPrefix(arg, "--")
|
||||
if after, ok := strings.CutPrefix(arg, "--"); ok {
|
||||
flag = after
|
||||
if i := strings.Index(flag, "="); i > 0 {
|
||||
flag = flag[:i]
|
||||
}
|
||||
@@ -348,10 +349,8 @@ func validateImageFile(imagePath string) error {
|
||||
ext := strings.ToLower(filepath.Ext(imagePath))
|
||||
validExtensions := []string{".png", ".jpeg", ".jpg", ".webp"}
|
||||
|
||||
for _, validExt := range validExtensions {
|
||||
if ext == validExt {
|
||||
return nil // Valid extension found
|
||||
}
|
||||
if slices.Contains(validExtensions, ext) {
|
||||
return nil // Valid extension found
|
||||
}
|
||||
|
||||
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_file_extension"), ext))
|
||||
@@ -370,13 +369,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
|
||||
// Validate size
|
||||
if size != "" {
|
||||
validSizes := []string{"1024x1024", "1536x1024", "1024x1536", "auto"}
|
||||
valid := false
|
||||
for _, validSize := range validSizes {
|
||||
if size == validSize {
|
||||
valid = true
|
||||
break
|
||||
}
|
||||
}
|
||||
valid := slices.Contains(validSizes, size)
|
||||
if !valid {
|
||||
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_size"), size))
|
||||
}
|
||||
@@ -385,13 +378,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
|
||||
// Validate quality
|
||||
if quality != "" {
|
||||
validQualities := []string{"low", "medium", "high", "auto"}
|
||||
valid := false
|
||||
for _, validQuality := range validQualities {
|
||||
if quality == validQuality {
|
||||
valid = true
|
||||
break
|
||||
}
|
||||
}
|
||||
valid := slices.Contains(validQualities, quality)
|
||||
if !valid {
|
||||
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_quality"), quality))
|
||||
}
|
||||
@@ -400,13 +387,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
|
||||
// Validate background
|
||||
if background != "" {
|
||||
validBackgrounds := []string{"opaque", "transparent"}
|
||||
valid := false
|
||||
for _, validBackground := range validBackgrounds {
|
||||
if background == validBackground {
|
||||
valid = true
|
||||
break
|
||||
}
|
||||
}
|
||||
valid := slices.Contains(validBackgrounds, background)
|
||||
if !valid {
|
||||
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_background"), background))
|
||||
}
|
||||
|
||||
@@ -137,8 +137,7 @@ func (h *TranslatedHelpWriter) getTranslatedDescription(flagName string) string
|
||||
|
||||
// getOriginalDescription retrieves the original description from struct tags
|
||||
func (h *TranslatedHelpWriter) getOriginalDescription(flagName string) string {
|
||||
flags := &Flags{}
|
||||
flagsType := reflect.TypeOf(flags).Elem()
|
||||
flagsType := reflect.TypeFor[Flags]()
|
||||
|
||||
for i := 0; i < flagsType.NumField(); i++ {
|
||||
field := flagsType.Field(i)
|
||||
@@ -184,10 +183,10 @@ func detectLanguageFromArgs() string {
|
||||
if i+1 < len(args) {
|
||||
return args[i+1]
|
||||
}
|
||||
} else if strings.HasPrefix(arg, "--language=") {
|
||||
return strings.TrimPrefix(arg, "--language=")
|
||||
} else if strings.HasPrefix(arg, "-g=") {
|
||||
return strings.TrimPrefix(arg, "-g=")
|
||||
} else if after, ok := strings.CutPrefix(arg, "--language="); ok {
|
||||
return after
|
||||
} else if after, ok := strings.CutPrefix(arg, "-g="); ok {
|
||||
return after
|
||||
} else if runtime.GOOS == "windows" && strings.HasPrefix(arg, "/g:") {
|
||||
return strings.TrimPrefix(arg, "/g:")
|
||||
} else if runtime.GOOS == "windows" && strings.HasPrefix(arg, "/g=") {
|
||||
@@ -218,8 +217,7 @@ func detectLanguageFromEnv() string {
|
||||
// writeAllFlags writes all flags with translated descriptions
|
||||
func (h *TranslatedHelpWriter) writeAllFlags() {
|
||||
// Use direct reflection on the Flags struct to get all flag definitions
|
||||
flags := &Flags{}
|
||||
flagsType := reflect.TypeOf(flags).Elem()
|
||||
flagsType := reflect.TypeFor[Flags]()
|
||||
|
||||
for i := 0; i < flagsType.NumField(); i++ {
|
||||
field := flagsType.Field(i)
|
||||
@@ -274,10 +272,7 @@ func (h *TranslatedHelpWriter) writeAllFlags() {
|
||||
|
||||
// Pad to align descriptions
|
||||
flagStr := flagLine.String()
|
||||
padding := 34 - len(flagStr)
|
||||
if padding < 2 {
|
||||
padding = 2
|
||||
}
|
||||
padding := max(34-len(flagStr), 2)
|
||||
|
||||
fmt.Fprintf(h.writer, "%s%s%s", flagStr, strings.Repeat(" ", padding), description)
|
||||
|
||||
|
||||
@@ -4,6 +4,7 @@ import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"slices"
|
||||
"strings"
|
||||
|
||||
"github.com/atotto/clipboard"
|
||||
@@ -66,10 +67,5 @@ func CreateAudioOutputFile(audioData []byte, fileName string) (err error) {
|
||||
func IsAudioFormat(fileName string) bool {
|
||||
ext := strings.ToLower(filepath.Ext(fileName))
|
||||
audioExts := []string{".wav", ".mp3", ".m4a", ".aac", ".ogg", ".flac"}
|
||||
for _, audioExt := range audioExts {
|
||||
if ext == audioExt {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
return slices.Contains(audioExts, ext)
|
||||
}
|
||||
|
||||
@@ -5,6 +5,7 @@ import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"slices"
|
||||
"strings"
|
||||
)
|
||||
|
||||
@@ -146,14 +147,7 @@ func fixInvalidEscapes(jsonStr string) string {
|
||||
// Check for escape sequences only inside strings
|
||||
if inQuotes && ch == '\\' && i+1 < len(jsonStr) {
|
||||
nextChar := jsonStr[i+1]
|
||||
isValid := false
|
||||
|
||||
for _, validEscape := range validEscapes {
|
||||
if nextChar == validEscape {
|
||||
isValid = true
|
||||
break
|
||||
}
|
||||
}
|
||||
isValid := slices.Contains(validEscapes, nextChar)
|
||||
|
||||
if !isValid {
|
||||
// Invalid escape sequence - add an extra backslash
|
||||
|
||||
@@ -51,7 +51,7 @@ func LevelFromInt(i int) Level {
|
||||
}
|
||||
|
||||
// Debug writes a debug message if the global level permits.
|
||||
func Debug(l Level, format string, a ...interface{}) {
|
||||
func Debug(l Level, format string, a ...any) {
|
||||
mu.RLock()
|
||||
current := level
|
||||
w := output
|
||||
@@ -63,7 +63,7 @@ func Debug(l Level, format string, a ...interface{}) {
|
||||
|
||||
// Log writes a message unconditionally to stderr.
|
||||
// This is for important messages that should always be shown regardless of debug level.
|
||||
func Log(format string, a ...interface{}) {
|
||||
func Log(format string, a ...any) {
|
||||
mu.RLock()
|
||||
w := output
|
||||
mu.RUnlock()
|
||||
|
||||
@@ -4,6 +4,7 @@ import (
|
||||
"context"
|
||||
"fmt"
|
||||
"net/http"
|
||||
"os"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
@@ -50,6 +51,10 @@ func NewClient() (ret *Client) {
|
||||
string(anthropic.ModelClaudeOpus4_1_20250805),
|
||||
string(anthropic.ModelClaudeSonnet4_5),
|
||||
string(anthropic.ModelClaudeSonnet4_5_20250929),
|
||||
string(anthropic.ModelClaudeOpus4_5_20251101),
|
||||
string(anthropic.ModelClaudeOpus4_5),
|
||||
string(anthropic.ModelClaudeHaiku4_5),
|
||||
string(anthropic.ModelClaudeHaiku4_5_20251001),
|
||||
}
|
||||
|
||||
ret.modelBetas = map[string][]string{
|
||||
@@ -212,7 +217,7 @@ func (an *Client) SendStream(
|
||||
}
|
||||
|
||||
if stream.Err() != nil {
|
||||
fmt.Printf("Messages stream error: %v\n", stream.Err())
|
||||
fmt.Fprintf(os.Stderr, "Messages stream error: %v\n", stream.Err())
|
||||
}
|
||||
close(channel)
|
||||
return
|
||||
|
||||
@@ -52,7 +52,7 @@ func createExpiredToken(accessToken, refreshToken string) *util.OAuthToken {
|
||||
}
|
||||
|
||||
// mockTokenServer creates a mock OAuth token server for testing
|
||||
func mockTokenServer(_ *testing.T, responses map[string]interface{}) *httptest.Server {
|
||||
func mockTokenServer(_ *testing.T, responses map[string]any) *httptest.Server {
|
||||
return httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
|
||||
if r.URL.Path != "/v1/oauth/token" {
|
||||
http.NotFound(w, r)
|
||||
@@ -80,7 +80,7 @@ func mockTokenServer(_ *testing.T, responses map[string]interface{}) *httptest.S
|
||||
|
||||
w.Header().Set("Content-Type", "application/json")
|
||||
|
||||
if errorResp, ok := response.(map[string]interface{}); ok && errorResp["error"] != nil {
|
||||
if errorResp, ok := response.(map[string]any); ok && errorResp["error"] != nil {
|
||||
w.WriteHeader(http.StatusBadRequest)
|
||||
}
|
||||
|
||||
@@ -114,8 +114,8 @@ func TestGeneratePKCE(t *testing.T) {
|
||||
|
||||
func TestExchangeToken_Success(t *testing.T) {
|
||||
// Create mock server
|
||||
server := mockTokenServer(t, map[string]interface{}{
|
||||
"authorization_code": map[string]interface{}{
|
||||
server := mockTokenServer(t, map[string]any{
|
||||
"authorization_code": map[string]any{
|
||||
"access_token": "test_access_token",
|
||||
"refresh_token": "test_refresh_token",
|
||||
"expires_in": 3600,
|
||||
@@ -161,8 +161,8 @@ func TestRefreshToken_Success(t *testing.T) {
|
||||
os.WriteFile(tokenPath, data, 0600)
|
||||
|
||||
// Create mock server for refresh
|
||||
server := mockTokenServer(t, map[string]interface{}{
|
||||
"refresh_token": map[string]interface{}{
|
||||
server := mockTokenServer(t, map[string]any{
|
||||
"refresh_token": map[string]any{
|
||||
"access_token": "new_access_token",
|
||||
"refresh_token": "new_refresh_token",
|
||||
"expires_in": 3600,
|
||||
@@ -416,7 +416,7 @@ func TestGetValidTokenWithValidToken(t *testing.T) {
|
||||
|
||||
// Benchmark tests
|
||||
func BenchmarkGeneratePKCE(b *testing.B) {
|
||||
for i := 0; i < b.N; i++ {
|
||||
for b.Loop() {
|
||||
_, _, err := generatePKCE()
|
||||
if err != nil {
|
||||
b.Fatal(err)
|
||||
@@ -427,8 +427,7 @@ func BenchmarkGeneratePKCE(b *testing.B) {
|
||||
func BenchmarkTokenIsExpired(b *testing.B) {
|
||||
token := createTestToken("access", "refresh", 3600)
|
||||
|
||||
b.ResetTimer()
|
||||
for i := 0; i < b.N; i++ {
|
||||
for b.Loop() {
|
||||
token.IsExpired(5)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -3,6 +3,7 @@ package gemini
|
||||
import (
|
||||
"fmt"
|
||||
"sort"
|
||||
"strings"
|
||||
)
|
||||
|
||||
// GeminiVoice represents a Gemini TTS voice with its characteristics
|
||||
@@ -126,16 +127,17 @@ func ListGeminiVoices(shellCompleteMode bool) string {
|
||||
if shellCompleteMode {
|
||||
// For shell completion, just return voice names
|
||||
names := GetGeminiVoiceNames()
|
||||
result := ""
|
||||
var result strings.Builder
|
||||
for _, name := range names {
|
||||
result += name + "\n"
|
||||
result.WriteString(name + "\n")
|
||||
}
|
||||
return result
|
||||
return result.String()
|
||||
}
|
||||
|
||||
// For human-readable output
|
||||
voices := GetGeminiVoices()
|
||||
result := "Available Gemini Text-to-Speech voices:\n\n"
|
||||
var result strings.Builder
|
||||
result.WriteString("Available Gemini Text-to-Speech voices:\n\n")
|
||||
|
||||
// Group by characteristics for better readability
|
||||
groups := map[string][]GeminiVoice{
|
||||
@@ -186,22 +188,22 @@ func ListGeminiVoices(shellCompleteMode bool) string {
|
||||
// Output grouped voices
|
||||
for groupName, groupVoices := range groups {
|
||||
if len(groupVoices) > 0 {
|
||||
result += fmt.Sprintf("%s:\n", groupName)
|
||||
result.WriteString(fmt.Sprintf("%s:\n", groupName))
|
||||
for _, voice := range groupVoices {
|
||||
defaultStr := ""
|
||||
if voice.Name == "Kore" {
|
||||
defaultStr = " (default)"
|
||||
}
|
||||
result += fmt.Sprintf(" %-15s - %s%s\n", voice.Name, voice.Description, defaultStr)
|
||||
result.WriteString(fmt.Sprintf(" %-15s - %s%s\n", voice.Name, voice.Description, defaultStr))
|
||||
}
|
||||
result += "\n"
|
||||
result.WriteString("\n")
|
||||
}
|
||||
}
|
||||
|
||||
result += "Use --voice <voice_name> to select a specific voice.\n"
|
||||
result += "Example: fabric --voice Charon -m gemini-2.5-flash-preview-tts -o output.wav \"Hello world\"\n"
|
||||
result.WriteString("Use --voice <voice_name> to select a specific voice.\n")
|
||||
result.WriteString("Example: fabric --voice Charon -m gemini-2.5-flash-preview-tts -o output.wav \"Hello world\"\n")
|
||||
|
||||
return result
|
||||
return result.String()
|
||||
}
|
||||
|
||||
// NOTE: This implementation maintains a curated list based on official Google documentation.
|
||||
|
||||
@@ -90,7 +90,7 @@ func (c *Client) ListModels() ([]string, error) {
|
||||
func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) (err error) {
|
||||
url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
|
||||
|
||||
payload := map[string]interface{}{
|
||||
payload := map[string]any{
|
||||
"messages": msgs,
|
||||
"model": opts.Model,
|
||||
"stream": true, // Enable streaming
|
||||
@@ -140,27 +140,27 @@ func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
|
||||
continue
|
||||
}
|
||||
|
||||
if bytes.HasPrefix(line, []byte("data: ")) {
|
||||
line = bytes.TrimPrefix(line, []byte("data: "))
|
||||
if after, ok := bytes.CutPrefix(line, []byte("data: ")); ok {
|
||||
line = after
|
||||
}
|
||||
|
||||
if string(line) == "[DONE]" {
|
||||
break
|
||||
}
|
||||
|
||||
var result map[string]interface{}
|
||||
var result map[string]any
|
||||
if err = json.Unmarshal(line, &result); err != nil {
|
||||
continue
|
||||
}
|
||||
|
||||
var choices []interface{}
|
||||
var choices []any
|
||||
var ok bool
|
||||
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
|
||||
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
|
||||
continue
|
||||
}
|
||||
|
||||
var delta map[string]interface{}
|
||||
if delta, ok = choices[0].(map[string]interface{})["delta"].(map[string]interface{}); !ok {
|
||||
var delta map[string]any
|
||||
if delta, ok = choices[0].(map[string]any)["delta"].(map[string]any); !ok {
|
||||
continue
|
||||
}
|
||||
|
||||
@@ -176,7 +176,7 @@ func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
|
||||
func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (content string, err error) {
|
||||
url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
|
||||
|
||||
payload := map[string]interface{}{
|
||||
payload := map[string]any{
|
||||
"messages": msgs,
|
||||
"model": opts.Model,
|
||||
// Add other options from opts if supported by LM Studio
|
||||
@@ -208,21 +208,21 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
|
||||
return
|
||||
}
|
||||
|
||||
var result map[string]interface{}
|
||||
var result map[string]any
|
||||
if err = json.NewDecoder(resp.Body).Decode(&result); err != nil {
|
||||
err = fmt.Errorf("failed to decode response: %w", err)
|
||||
return
|
||||
}
|
||||
|
||||
var choices []interface{}
|
||||
var choices []any
|
||||
var ok bool
|
||||
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
|
||||
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
|
||||
err = fmt.Errorf("invalid response format: missing or empty choices")
|
||||
return
|
||||
}
|
||||
|
||||
var message map[string]interface{}
|
||||
if message, ok = choices[0].(map[string]interface{})["message"].(map[string]interface{}); !ok {
|
||||
var message map[string]any
|
||||
if message, ok = choices[0].(map[string]any)["message"].(map[string]any); !ok {
|
||||
err = fmt.Errorf("invalid response format: missing message in first choice")
|
||||
return
|
||||
}
|
||||
@@ -238,7 +238,7 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
|
||||
func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatOptions) (text string, err error) {
|
||||
url := fmt.Sprintf("%s/completions", c.ApiUrl.Value)
|
||||
|
||||
payload := map[string]interface{}{
|
||||
payload := map[string]any{
|
||||
"prompt": prompt,
|
||||
"model": opts.Model,
|
||||
// Add other options from opts if supported by LM Studio
|
||||
@@ -270,20 +270,20 @@ func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatO
|
||||
return
|
||||
}
|
||||
|
||||
var result map[string]interface{}
|
||||
var result map[string]any
|
||||
if err = json.NewDecoder(resp.Body).Decode(&result); err != nil {
|
||||
err = fmt.Errorf("failed to decode response: %w", err)
|
||||
return
|
||||
}
|
||||
|
||||
var choices []interface{}
|
||||
var choices []any
|
||||
var ok bool
|
||||
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
|
||||
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
|
||||
err = fmt.Errorf("invalid response format: missing or empty choices")
|
||||
return
|
||||
}
|
||||
|
||||
if text, ok = choices[0].(map[string]interface{})["text"].(string); !ok {
|
||||
if text, ok = choices[0].(map[string]any)["text"].(string); !ok {
|
||||
err = fmt.Errorf("invalid response format: missing or non-string text in first choice")
|
||||
return
|
||||
}
|
||||
@@ -294,7 +294,7 @@ func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatO
|
||||
func (c *Client) GetEmbeddings(ctx context.Context, input string, opts *domain.ChatOptions) (embeddings []float64, err error) {
|
||||
url := fmt.Sprintf("%s/embeddings", c.ApiUrl.Value)
|
||||
|
||||
payload := map[string]interface{}{
|
||||
payload := map[string]any{
|
||||
"input": input,
|
||||
"model": opts.Model,
|
||||
// Add other options from opts if supported by LM Studio
|
||||
|
||||
@@ -2,7 +2,9 @@ package ollama
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/base64"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"net/url"
|
||||
"os"
|
||||
@@ -10,11 +12,10 @@ import (
|
||||
"time"
|
||||
|
||||
"github.com/danielmiessler/fabric/internal/chat"
|
||||
ollamaapi "github.com/ollama/ollama/api"
|
||||
"github.com/samber/lo"
|
||||
|
||||
"github.com/danielmiessler/fabric/internal/domain"
|
||||
debuglog "github.com/danielmiessler/fabric/internal/log"
|
||||
"github.com/danielmiessler/fabric/internal/plugins"
|
||||
ollamaapi "github.com/ollama/ollama/api"
|
||||
)
|
||||
|
||||
const defaultBaseUrl = "http://localhost:11434"
|
||||
@@ -48,6 +49,7 @@ type Client struct {
|
||||
apiUrl *url.URL
|
||||
client *ollamaapi.Client
|
||||
ApiHttpTimeout *plugins.SetupQuestion
|
||||
httpClient *http.Client
|
||||
}
|
||||
|
||||
type transport_sec struct {
|
||||
@@ -84,7 +86,8 @@ func (o *Client) configure() (err error) {
|
||||
}
|
||||
}
|
||||
|
||||
o.client = ollamaapi.NewClient(o.apiUrl, &http.Client{Timeout: timeout, Transport: &transport_sec{underlyingTransport: http.DefaultTransport, ApiKey: o.ApiKey}})
|
||||
o.httpClient = &http.Client{Timeout: timeout, Transport: &transport_sec{underlyingTransport: http.DefaultTransport, ApiKey: o.ApiKey}}
|
||||
o.client = ollamaapi.NewClient(o.apiUrl, o.httpClient)
|
||||
|
||||
return
|
||||
}
|
||||
@@ -104,15 +107,18 @@ func (o *Client) ListModels() (ret []string, err error) {
|
||||
}
|
||||
|
||||
func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) (err error) {
|
||||
req := o.createChatRequest(msgs, opts)
|
||||
ctx := context.Background()
|
||||
|
||||
var req ollamaapi.ChatRequest
|
||||
if req, err = o.createChatRequest(ctx, msgs, opts); err != nil {
|
||||
return
|
||||
}
|
||||
|
||||
respFunc := func(resp ollamaapi.ChatResponse) (streamErr error) {
|
||||
channel <- resp.Message.Content
|
||||
return
|
||||
}
|
||||
|
||||
ctx := context.Background()
|
||||
|
||||
if err = o.client.Chat(ctx, &req, respFunc); err != nil {
|
||||
return
|
||||
}
|
||||
@@ -124,7 +130,10 @@ func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
|
||||
func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret string, err error) {
|
||||
bf := false
|
||||
|
||||
req := o.createChatRequest(msgs, opts)
|
||||
var req ollamaapi.ChatRequest
|
||||
if req, err = o.createChatRequest(ctx, msgs, opts); err != nil {
|
||||
return
|
||||
}
|
||||
req.Stream = &bf
|
||||
|
||||
respFunc := func(resp ollamaapi.ChatResponse) (streamErr error) {
|
||||
@@ -133,17 +142,20 @@ func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
|
||||
}
|
||||
|
||||
if err = o.client.Chat(ctx, &req, respFunc); err != nil {
|
||||
fmt.Printf("FRED --> %s\n", err)
|
||||
debuglog.Debug(debuglog.Basic, "Ollama chat request failed: %v\n", err)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
func (o *Client) createChatRequest(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret ollamaapi.ChatRequest) {
|
||||
messages := lo.Map(msgs, func(message *chat.ChatCompletionMessage, _ int) (ret ollamaapi.Message) {
|
||||
return ollamaapi.Message{Role: message.Role, Content: message.Content}
|
||||
})
|
||||
func (o *Client) createChatRequest(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret ollamaapi.ChatRequest, err error) {
|
||||
messages := make([]ollamaapi.Message, len(msgs))
|
||||
for i, message := range msgs {
|
||||
if messages[i], err = o.convertMessage(ctx, message); err != nil {
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
options := map[string]interface{}{
|
||||
options := map[string]any{
|
||||
"temperature": opts.Temperature,
|
||||
"presence_penalty": opts.PresencePenalty,
|
||||
"frequency_penalty": opts.FrequencyPenalty,
|
||||
@@ -162,14 +174,85 @@ func (o *Client) createChatRequest(msgs []*chat.ChatCompletionMessage, opts *dom
|
||||
return
|
||||
}
|
||||
|
||||
func (o *Client) convertMessage(ctx context.Context, message *chat.ChatCompletionMessage) (ret ollamaapi.Message, err error) {
|
||||
ret = ollamaapi.Message{Role: message.Role, Content: message.Content}
|
||||
|
||||
if len(message.MultiContent) == 0 {
|
||||
return
|
||||
}
|
||||
|
||||
// Pre-allocate with capacity hint
|
||||
textParts := make([]string, 0, len(message.MultiContent))
|
||||
if strings.TrimSpace(ret.Content) != "" {
|
||||
textParts = append(textParts, strings.TrimSpace(ret.Content))
|
||||
}
|
||||
|
||||
for _, part := range message.MultiContent {
|
||||
switch part.Type {
|
||||
case chat.ChatMessagePartTypeText:
|
||||
if trimmed := strings.TrimSpace(part.Text); trimmed != "" {
|
||||
textParts = append(textParts, trimmed)
|
||||
}
|
||||
case chat.ChatMessagePartTypeImageURL:
|
||||
// Nil guard
|
||||
if part.ImageURL == nil || part.ImageURL.URL == "" {
|
||||
continue
|
||||
}
|
||||
var img []byte
|
||||
if img, err = o.loadImageBytes(ctx, part.ImageURL.URL); err != nil {
|
||||
return
|
||||
}
|
||||
ret.Images = append(ret.Images, ollamaapi.ImageData(img))
|
||||
}
|
||||
}
|
||||
|
||||
ret.Content = strings.Join(textParts, "\n")
|
||||
return
|
||||
}
|
||||
|
||||
func (o *Client) loadImageBytes(ctx context.Context, imageURL string) (ret []byte, err error) {
|
||||
// Handle data URLs (base64 encoded)
|
||||
if strings.HasPrefix(imageURL, "data:") {
|
||||
parts := strings.SplitN(imageURL, ",", 2)
|
||||
if len(parts) != 2 {
|
||||
err = fmt.Errorf("invalid data URL format")
|
||||
return
|
||||
}
|
||||
if ret, err = base64.StdEncoding.DecodeString(parts[1]); err != nil {
|
||||
err = fmt.Errorf("failed to decode data URL: %w", err)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle HTTP URLs with context
|
||||
var req *http.Request
|
||||
if req, err = http.NewRequestWithContext(ctx, http.MethodGet, imageURL, nil); err != nil {
|
||||
return
|
||||
}
|
||||
|
||||
var resp *http.Response
|
||||
if resp, err = o.httpClient.Do(req); err != nil {
|
||||
return
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
if resp.StatusCode >= http.StatusBadRequest {
|
||||
err = fmt.Errorf("failed to fetch image %s: %s", imageURL, resp.Status)
|
||||
return
|
||||
}
|
||||
|
||||
ret, err = io.ReadAll(resp.Body)
|
||||
return
|
||||
}
|
||||
|
||||
func (o *Client) NeedsRawMode(modelName string) bool {
|
||||
ollamaPrefixes := []string{
|
||||
ollamaSearchStrings := []string{
|
||||
"llama3",
|
||||
"llama2",
|
||||
"mistral",
|
||||
}
|
||||
for _, prefix := range ollamaPrefixes {
|
||||
if strings.HasPrefix(modelName, prefix) {
|
||||
for _, searchString := range ollamaSearchStrings {
|
||||
if strings.Contains(modelName, searchString) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
@@ -172,10 +172,11 @@ func (o *Client) supportsResponsesAPI() bool {
|
||||
|
||||
func (o *Client) NeedsRawMode(modelName string) bool {
|
||||
openaiModelsPrefixes := []string{
|
||||
"glm",
|
||||
"gpt-5",
|
||||
"o1",
|
||||
"o3",
|
||||
"o4",
|
||||
"gpt-5",
|
||||
}
|
||||
openAIModelsNeedingRaw := []string{
|
||||
"gpt-4o-mini-search-preview",
|
||||
|
||||
@@ -8,6 +8,7 @@ import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"slices"
|
||||
"strings"
|
||||
|
||||
"github.com/danielmiessler/fabric/internal/domain"
|
||||
@@ -31,12 +32,7 @@ var ImageGenerationSupportedModels = []string{
|
||||
|
||||
// supportsImageGeneration checks if the given model supports the image_generation tool
|
||||
func supportsImageGeneration(model string) bool {
|
||||
for _, supportedModel := range ImageGenerationSupportedModels {
|
||||
if model == supportedModel {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
return slices.Contains(ImageGenerationSupportedModels, model)
|
||||
}
|
||||
|
||||
// getOutputFormatFromExtension determines the API output format based on file extension
|
||||
|
||||
@@ -345,7 +345,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
opts *domain.ChatOptions
|
||||
expected map[string]interface{}
|
||||
expected map[string]any
|
||||
}{
|
||||
{
|
||||
name: "All parameters specified",
|
||||
@@ -356,7 +356,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
|
||||
ImageBackground: "transparent",
|
||||
ImageCompression: 0, // Not applicable for PNG
|
||||
},
|
||||
expected: map[string]interface{}{
|
||||
expected: map[string]any{
|
||||
"size": "1536x1024",
|
||||
"quality": "high",
|
||||
"background": "transparent",
|
||||
@@ -372,7 +372,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
|
||||
ImageBackground: "opaque",
|
||||
ImageCompression: 75,
|
||||
},
|
||||
expected: map[string]interface{}{
|
||||
expected: map[string]any{
|
||||
"size": "1024x1024",
|
||||
"quality": "medium",
|
||||
"background": "opaque",
|
||||
@@ -386,7 +386,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
|
||||
ImageFile: "/tmp/test.webp",
|
||||
ImageQuality: "low",
|
||||
},
|
||||
expected: map[string]interface{}{
|
||||
expected: map[string]any{
|
||||
"quality": "low",
|
||||
"output_format": "webp",
|
||||
},
|
||||
@@ -396,7 +396,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
|
||||
opts: &domain.ChatOptions{
|
||||
ImageFile: "/tmp/test.png",
|
||||
},
|
||||
expected: map[string]interface{}{
|
||||
expected: map[string]any{
|
||||
"output_format": "png",
|
||||
},
|
||||
},
|
||||
|
||||
@@ -16,7 +16,7 @@ func TestBuildResponseRequestWithMaxTokens(t *testing.T) {
|
||||
|
||||
var msgs []*chat.ChatCompletionMessage
|
||||
|
||||
for i := 0; i < 2; i++ {
|
||||
for range 2 {
|
||||
msgs = append(msgs, &chat.ChatCompletionMessage{
|
||||
Role: "User",
|
||||
Content: "My msg",
|
||||
@@ -42,7 +42,7 @@ func TestBuildResponseRequestNoMaxTokens(t *testing.T) {
|
||||
|
||||
var msgs []*chat.ChatCompletionMessage
|
||||
|
||||
for i := 0; i < 2; i++ {
|
||||
for range 2 {
|
||||
msgs = append(msgs, &chat.ChatCompletionMessage{
|
||||
Role: "User",
|
||||
Content: "My msg",
|
||||
|
||||
@@ -2,6 +2,7 @@ package openai_compatible
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"strings"
|
||||
|
||||
@@ -38,8 +39,12 @@ func NewClient(providerConfig ProviderConfig) *Client {
|
||||
|
||||
// ListModels overrides the default ListModels to handle different response formats
|
||||
func (c *Client) ListModels() ([]string, error) {
|
||||
// If a custom models URL is provided, use direct fetch with that URL
|
||||
// If a custom models URL is provided, handle it
|
||||
if c.modelsURL != "" {
|
||||
// Check for static model list
|
||||
if strings.HasPrefix(c.modelsURL, "static:") {
|
||||
return c.getStaticModels(c.modelsURL)
|
||||
}
|
||||
// TODO: Handle context properly in Fabric by accepting and propagating a context.Context
|
||||
// instead of creating a new one here.
|
||||
return openai.FetchModelsDirectly(context.Background(), c.modelsURL, c.Client.ApiKey.Value, c.GetName())
|
||||
@@ -55,6 +60,68 @@ func (c *Client) ListModels() ([]string, error) {
|
||||
return c.DirectlyGetModels(context.Background())
|
||||
}
|
||||
|
||||
// getStaticModels returns a predefined list of models for providers that don't support model discovery
|
||||
func (c *Client) getStaticModels(modelsKey string) ([]string, error) {
|
||||
switch modelsKey {
|
||||
case "static:abacus":
|
||||
return []string{
|
||||
"route-llm",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-mini",
|
||||
"o4-mini",
|
||||
"o3-pro",
|
||||
"o3",
|
||||
"o3-mini",
|
||||
"gpt-4.1",
|
||||
"gpt-4.1-mini",
|
||||
"gpt-4.1-nano",
|
||||
"gpt-5",
|
||||
"gpt-5-mini",
|
||||
"gpt-5-nano",
|
||||
"gpt-5.1",
|
||||
"gpt-5.1-chat-latest",
|
||||
"openai/gpt-oss-120b",
|
||||
"claude-3-7-sonnet-20250219",
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-opus-4-20250514",
|
||||
"claude-opus-4-1-20250805",
|
||||
"claude-sonnet-4-5-20250929",
|
||||
"claude-haiku-4-5-20251001",
|
||||
"claude-opus-4-5-20251101",
|
||||
"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
|
||||
"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
|
||||
"meta-llama/Meta-Llama-3.1-70B-Instruct",
|
||||
"meta-llama/Meta-Llama-3.1-8B-Instruct",
|
||||
"llama-3.3-70b-versatile",
|
||||
"gemini-2.0-flash-001",
|
||||
"gemini-2.0-pro-exp-02-05",
|
||||
"gemini-2.5-pro",
|
||||
"gemini-2.5-flash",
|
||||
"gemini-3-pro-preview",
|
||||
"qwen-2.5-coder-32b",
|
||||
"Qwen/Qwen2.5-72B-Instruct",
|
||||
"Qwen/QwQ-32B",
|
||||
"Qwen/Qwen3-235B-A22B-Instruct-2507",
|
||||
"Qwen/Qwen3-32B",
|
||||
"qwen/qwen3-coder-480b-a35b-instruct",
|
||||
"qwen/qwen3-Max",
|
||||
"grok-4-0709",
|
||||
"grok-4-fast-non-reasoning",
|
||||
"grok-4-1-fast-non-reasoning",
|
||||
"grok-code-fast-1",
|
||||
"kimi-k2-turbo-preview",
|
||||
"deepseek/deepseek-v3.1",
|
||||
"deepseek-ai/DeepSeek-V3.1-Terminus",
|
||||
"deepseek-ai/DeepSeek-R1",
|
||||
"deepseek-ai/DeepSeek-V3.2",
|
||||
"zai-org/glm-4.5",
|
||||
"zai-org/glm-4.6",
|
||||
}, nil
|
||||
default:
|
||||
return nil, fmt.Errorf("unknown static model list: %s", modelsKey)
|
||||
}
|
||||
}
|
||||
|
||||
// ProviderMap is a map of provider name to ProviderConfig for O(1) lookup
|
||||
var ProviderMap = map[string]ProviderConfig{
|
||||
"AIML": {
|
||||
@@ -123,6 +190,17 @@ var ProviderMap = map[string]ProviderConfig{
|
||||
BaseURL: "https://api.venice.ai/api/v1",
|
||||
ImplementsResponses: false,
|
||||
},
|
||||
"Z AI": {
|
||||
Name: "Z AI",
|
||||
BaseURL: "https://api.z.ai/api/paas/v4",
|
||||
ImplementsResponses: false,
|
||||
},
|
||||
"Abacus": {
|
||||
Name: "Abacus",
|
||||
BaseURL: "https://routellm.abacus.ai/v1/",
|
||||
ModelsURL: "static:abacus", // Special marker for static model list
|
||||
ImplementsResponses: false,
|
||||
},
|
||||
}
|
||||
|
||||
// GetProviderByName returns the provider configuration for a given name with O(1) lookup
|
||||
|
||||
@@ -20,6 +20,16 @@ func TestCreateClient(t *testing.T) {
|
||||
provider: "Groq",
|
||||
exists: true,
|
||||
},
|
||||
{
|
||||
name: "Existing provider - Z AI",
|
||||
provider: "Z AI",
|
||||
exists: true,
|
||||
},
|
||||
{
|
||||
name: "Existing provider - Abacus",
|
||||
provider: "Abacus",
|
||||
exists: true,
|
||||
},
|
||||
{
|
||||
name: "Non-existent provider",
|
||||
provider: "NonExistent",
|
||||
|
||||
@@ -4,6 +4,7 @@ import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"github.com/danielmiessler/fabric/internal/domain"
|
||||
@@ -107,18 +108,19 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
|
||||
return "", fmt.Errorf("perplexity API request failed: %w", err) // Corrected capitalization
|
||||
}
|
||||
|
||||
content := resp.GetLastContent()
|
||||
var content strings.Builder
|
||||
content.WriteString(resp.GetLastContent())
|
||||
|
||||
// Append citations if available
|
||||
citations := resp.GetCitations()
|
||||
if len(citations) > 0 {
|
||||
content += "\n\n# CITATIONS\n\n"
|
||||
content.WriteString("\n\n# CITATIONS\n\n")
|
||||
for i, citation := range citations {
|
||||
content += fmt.Sprintf("- [%d] %s\n", i+1, citation)
|
||||
content.WriteString(fmt.Sprintf("- [%d] %s\n", i+1, citation))
|
||||
}
|
||||
}
|
||||
|
||||
return content, nil
|
||||
return content.String(), nil
|
||||
}
|
||||
|
||||
func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) error {
|
||||
|
||||
@@ -134,7 +134,7 @@ func (o *StorageEntity) buildFileName(name string) string {
|
||||
return fmt.Sprintf("%s%v", name, o.FileExtension)
|
||||
}
|
||||
|
||||
func (o *StorageEntity) SaveAsJson(name string, item interface{}) (err error) {
|
||||
func (o *StorageEntity) SaveAsJson(name string, item any) (err error) {
|
||||
var jsonString []byte
|
||||
if jsonString, err = json.Marshal(item); err == nil {
|
||||
err = o.Save(name, jsonString)
|
||||
@@ -145,7 +145,7 @@ func (o *StorageEntity) SaveAsJson(name string, item interface{}) (err error) {
|
||||
return err
|
||||
}
|
||||
|
||||
func (o *StorageEntity) LoadAsJson(name string, item interface{}) (err error) {
|
||||
func (o *StorageEntity) LoadAsJson(name string, item any) (err error) {
|
||||
var content []byte
|
||||
if content, err = o.Load(name); err != nil {
|
||||
return
|
||||
|
||||
@@ -92,7 +92,11 @@ func (o *PluginBase) Setup() (err error) {
|
||||
return
|
||||
}
|
||||
|
||||
err = o.Configure()
|
||||
// After Setup, run ConfigureCustom if present, but skip re-validation
|
||||
// since Ask() already validated user input (or allowed explicit reset)
|
||||
if o.ConfigureCustom != nil {
|
||||
err = o.ConfigureCustom()
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
@@ -198,16 +202,21 @@ func (o *SetupQuestion) Ask(label string) (err error) {
|
||||
var answer string
|
||||
fmt.Scanln(&answer)
|
||||
answer = strings.TrimRight(answer, "\n")
|
||||
isReset := strings.ToLower(answer) == AnswerReset
|
||||
if answer == "" {
|
||||
answer = o.Value
|
||||
} else if strings.ToLower(answer) == AnswerReset {
|
||||
} else if isReset {
|
||||
answer = ""
|
||||
}
|
||||
err = o.OnAnswer(answer)
|
||||
err = o.OnAnswerWithReset(answer, isReset)
|
||||
return
|
||||
}
|
||||
|
||||
func (o *SetupQuestion) OnAnswer(answer string) (err error) {
|
||||
return o.OnAnswerWithReset(answer, false)
|
||||
}
|
||||
|
||||
func (o *SetupQuestion) OnAnswerWithReset(answer string, isReset bool) (err error) {
|
||||
if o.Type == SettingTypeBool {
|
||||
if answer == "" {
|
||||
o.Value = ""
|
||||
@@ -226,6 +235,11 @@ func (o *SetupQuestion) OnAnswer(answer string) (err error) {
|
||||
return
|
||||
}
|
||||
}
|
||||
// Skip validation when explicitly resetting a value - the user intentionally
|
||||
// wants to clear the value even if it's required
|
||||
if isReset {
|
||||
return nil
|
||||
}
|
||||
err = o.IsValidErr()
|
||||
return
|
||||
}
|
||||
|
||||
@@ -116,6 +116,91 @@ func TestSetupQuestion_Ask(t *testing.T) {
|
||||
assert.Equal(t, "user_value", setting.Value)
|
||||
}
|
||||
|
||||
func TestSetupQuestion_Ask_Reset(t *testing.T) {
|
||||
// Test that resetting a required field doesn't produce an error
|
||||
setting := &Setting{
|
||||
EnvVariable: "TEST_RESET_SETTING",
|
||||
Value: "existing_value",
|
||||
Required: true,
|
||||
}
|
||||
question := &SetupQuestion{
|
||||
Setting: setting,
|
||||
Question: "Enter test setting:",
|
||||
}
|
||||
input := "reset\n"
|
||||
fmtInput := captureInput(input)
|
||||
defer fmtInput()
|
||||
err := question.Ask("TestConfigurable")
|
||||
// Should NOT return an error even though the field is required
|
||||
assert.NoError(t, err)
|
||||
// Value should be cleared
|
||||
assert.Equal(t, "", setting.Value)
|
||||
}
|
||||
|
||||
func TestSetupQuestion_OnAnswerWithReset(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
setting *Setting
|
||||
answer string
|
||||
isReset bool
|
||||
expectError bool
|
||||
expectValue string
|
||||
}{
|
||||
{
|
||||
name: "reset required field should not error",
|
||||
setting: &Setting{
|
||||
EnvVariable: "TEST_SETTING",
|
||||
Value: "old_value",
|
||||
Required: true,
|
||||
},
|
||||
answer: "",
|
||||
isReset: true,
|
||||
expectError: false,
|
||||
expectValue: "",
|
||||
},
|
||||
{
|
||||
name: "empty answer on required field should error",
|
||||
setting: &Setting{
|
||||
EnvVariable: "TEST_SETTING",
|
||||
Value: "",
|
||||
Required: true,
|
||||
},
|
||||
answer: "",
|
||||
isReset: false,
|
||||
expectError: true,
|
||||
expectValue: "",
|
||||
},
|
||||
{
|
||||
name: "valid answer on required field should not error",
|
||||
setting: &Setting{
|
||||
EnvVariable: "TEST_SETTING",
|
||||
Value: "",
|
||||
Required: true,
|
||||
},
|
||||
answer: "new_value",
|
||||
isReset: false,
|
||||
expectError: false,
|
||||
expectValue: "new_value",
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
question := &SetupQuestion{
|
||||
Setting: tt.setting,
|
||||
Question: "Test question",
|
||||
}
|
||||
err := question.OnAnswerWithReset(tt.answer, tt.isReset)
|
||||
if tt.expectError {
|
||||
assert.Error(t, err)
|
||||
} else {
|
||||
assert.NoError(t, err)
|
||||
}
|
||||
assert.Equal(t, tt.expectValue, tt.setting.Value)
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
func TestSettings_IsConfigured(t *testing.T) {
|
||||
settings := Settings{
|
||||
{EnvVariable: "TEST_SETTING1", Value: "value1", Required: true},
|
||||
|
||||
@@ -187,9 +187,10 @@ esac`
|
||||
executor := NewExtensionExecutor(registry)
|
||||
|
||||
// Helper function to create and register extension
|
||||
createExtension := func(name, opName, cmdTemplate string, config map[string]interface{}) error {
|
||||
createExtension := func(name, opName, cmdTemplate string, config map[string]any) error {
|
||||
configPath := filepath.Join(tmpDir, name+".yaml")
|
||||
configContent := `name: ` + name + `
|
||||
var configContent strings.Builder
|
||||
configContent.WriteString(`name: ` + name + `
|
||||
executable: ` + testScript + `
|
||||
type: executable
|
||||
timeout: 30s
|
||||
@@ -199,14 +200,14 @@ operations:
|
||||
config:
|
||||
output:
|
||||
method: file
|
||||
file_config:`
|
||||
file_config:`)
|
||||
|
||||
// Add config options
|
||||
for k, v := range config {
|
||||
configContent += "\n " + k + ": " + strings.TrimSpace(v.(string))
|
||||
configContent.WriteString("\n " + k + ": " + strings.TrimSpace(v.(string)))
|
||||
}
|
||||
|
||||
if err := os.WriteFile(configPath, []byte(configContent), 0644); err != nil {
|
||||
if err := os.WriteFile(configPath, []byte(configContent.String()), 0644); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
@@ -216,7 +217,7 @@ config:
|
||||
// Test basic fixed file output
|
||||
t.Run("BasicFixedFile", func(t *testing.T) {
|
||||
outputFile := filepath.Join(tmpDir, "output.txt")
|
||||
config := map[string]interface{}{
|
||||
config := map[string]any{
|
||||
"output_file": `"output.txt"`,
|
||||
"work_dir": `"` + tmpDir + `"`,
|
||||
"cleanup": "true",
|
||||
@@ -241,7 +242,7 @@ config:
|
||||
|
||||
// Test no work_dir specified
|
||||
t.Run("NoWorkDir", func(t *testing.T) {
|
||||
config := map[string]interface{}{
|
||||
config := map[string]any{
|
||||
"output_file": `"direct-output.txt"`,
|
||||
"cleanup": "true",
|
||||
}
|
||||
@@ -263,7 +264,7 @@ config:
|
||||
outputFile := filepath.Join(tmpDir, "cleanup-test.txt")
|
||||
|
||||
// Test with cleanup enabled
|
||||
config := map[string]interface{}{
|
||||
config := map[string]any{
|
||||
"output_file": `"cleanup-test.txt"`,
|
||||
"work_dir": `"` + tmpDir + `"`,
|
||||
"cleanup": "true",
|
||||
@@ -307,7 +308,7 @@ config:
|
||||
// Test error cases
|
||||
t.Run("ErrorCases", func(t *testing.T) {
|
||||
outputFile := filepath.Join(tmpDir, "error-test.txt")
|
||||
config := map[string]interface{}{
|
||||
config := map[string]any{
|
||||
"output_file": `"error-test.txt"`,
|
||||
"work_dir": `"` + tmpDir + `"`,
|
||||
"cleanup": "true",
|
||||
@@ -341,7 +342,7 @@ config:
|
||||
|
||||
// Test with missing output_file
|
||||
t.Run("MissingOutputFile", func(t *testing.T) {
|
||||
config := map[string]interface{}{
|
||||
config := map[string]any{
|
||||
"work_dir": `"` + tmpDir + `"`,
|
||||
"cleanup": "true",
|
||||
}
|
||||
|
||||
@@ -30,7 +30,7 @@ type ExtensionDefinition struct {
|
||||
Operations map[string]OperationConfig `yaml:"operations"`
|
||||
|
||||
// Additional config
|
||||
Config map[string]interface{} `yaml:"config"`
|
||||
Config map[string]any `yaml:"config"`
|
||||
}
|
||||
|
||||
type OperationConfig struct {
|
||||
@@ -53,7 +53,7 @@ type ExtensionRegistry struct {
|
||||
|
||||
// Helper methods for Config access
|
||||
func (e *ExtensionDefinition) GetOutputMethod() string {
|
||||
if output, ok := e.Config["output"].(map[string]interface{}); ok {
|
||||
if output, ok := e.Config["output"].(map[string]any); ok {
|
||||
if method, ok := output["method"].(string); ok {
|
||||
return method
|
||||
}
|
||||
@@ -61,9 +61,9 @@ func (e *ExtensionDefinition) GetOutputMethod() string {
|
||||
return "stdout" // default to stdout if not specified
|
||||
}
|
||||
|
||||
func (e *ExtensionDefinition) GetFileConfig() map[string]interface{} {
|
||||
if output, ok := e.Config["output"].(map[string]interface{}); ok {
|
||||
if fileConfig, ok := output["file_config"].(map[string]interface{}); ok {
|
||||
func (e *ExtensionDefinition) GetFileConfig() map[string]any {
|
||||
if output, ok := e.Config["output"].(map[string]any); ok {
|
||||
if fileConfig, ok := output["file_config"].(map[string]any); ok {
|
||||
return fileConfig
|
||||
}
|
||||
}
|
||||
|
||||
@@ -33,7 +33,7 @@ func init() {
|
||||
var pluginPattern = regexp.MustCompile(`\{\{plugin:([^:]+):([^:]+)(?::([^}]+))?\}\}`)
|
||||
var extensionPattern = regexp.MustCompile(`\{\{ext:([^:]+):([^:]+)(?::([^}]+))?\}\}`)
|
||||
|
||||
func debugf(format string, a ...interface{}) {
|
||||
func debugf(format string, a ...any) {
|
||||
debuglog.Debug(debuglog.Trace, format, a...)
|
||||
}
|
||||
|
||||
|
||||
@@ -16,7 +16,7 @@ func toTitle(s string) string {
|
||||
lower := strings.ToLower(s)
|
||||
runes := []rune(lower)
|
||||
|
||||
for i := 0; i < len(runes); i++ {
|
||||
for i := range runes {
|
||||
// Capitalize if previous char is non-letter AND
|
||||
// (we're at the end OR next char is not space)
|
||||
if i == 0 || !unicode.IsLetter(runes[i-1]) {
|
||||
|
||||
@@ -24,7 +24,7 @@ func (h *ModelsHandler) GetModelNames(c *gin.Context) {
|
||||
return
|
||||
}
|
||||
|
||||
response := make(map[string]interface{})
|
||||
response := make(map[string]any)
|
||||
vendors := make(map[string][]string)
|
||||
|
||||
for _, groupItems := range vendorsModels.GroupsItems {
|
||||
|
||||
@@ -102,7 +102,7 @@ func ServeOllama(registry *core.PluginRegistry, address string, version string)
|
||||
// Ollama Endpoints
|
||||
r.GET("/api/tags", typeConversion.ollamaTags)
|
||||
r.GET("/api/version", func(c *gin.Context) {
|
||||
c.Data(200, "application/json", []byte(fmt.Sprintf("{\"%s\"}", version)))
|
||||
c.Data(200, "application/json", fmt.Appendf(nil, "{\"%s\"}", version))
|
||||
})
|
||||
r.POST("/api/chat", typeConversion.ollamaChat)
|
||||
|
||||
@@ -224,7 +224,7 @@ func (f APIConvert) ollamaChat(c *gin.Context) {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"error": "testing endpoint"})
|
||||
return
|
||||
}
|
||||
for _, word := range strings.Split(fabricResponse.Content, " ") {
|
||||
for word := range strings.SplitSeq(fabricResponse.Content, " ") {
|
||||
forwardedResponse = OllamaResponse{
|
||||
Model: "",
|
||||
CreatedAt: "",
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
package restapi
|
||||
|
||||
import (
|
||||
"maps"
|
||||
"net/http"
|
||||
|
||||
"github.com/danielmiessler/fabric/internal/plugins/db/fsdb"
|
||||
@@ -74,9 +75,7 @@ func (h *PatternsHandler) ApplyPattern(c *gin.Context) {
|
||||
variables[key] = values[0]
|
||||
}
|
||||
}
|
||||
for key, value := range request.Variables {
|
||||
variables[key] = value
|
||||
}
|
||||
maps.Copy(variables, request.Variables)
|
||||
|
||||
pattern, err := h.patterns.GetApplyVariables(name, variables, request.Input)
|
||||
if err != nil {
|
||||
|
||||
@@ -32,8 +32,8 @@ schema = 3
|
||||
version = "v1.3.3"
|
||||
hash = "sha256-jv7ZshpSd7FZzKKN6hqlUgiR8C3y85zNIS/hq7g76Ho="
|
||||
[mod."github.com/anthropics/anthropic-sdk-go"]
|
||||
version = "v1.16.0"
|
||||
hash = "sha256-hD6Ix+V5IBFfoaCuAZemrDQx/+G111fCYHn2FAxFuEE="
|
||||
version = "v1.19.0"
|
||||
hash = "sha256-ubYeau5XL0tx4c/79L58rzJGOdOWs9z6WQOtN6mpgxw="
|
||||
[mod."github.com/araddon/dateparse"]
|
||||
version = "v0.0.0-20210429162001-6b43995a97de"
|
||||
hash = "sha256-UuX84naeRGMsFOgIgRoBHG5sNy1CzBkWPKmd6VbLwFw="
|
||||
@@ -317,26 +317,26 @@ schema = 3
|
||||
version = "v0.18.0"
|
||||
hash = "sha256-tUpUPERjmRi7zldj0oPlnbnBhEkcI9iQGvP1HqlsK10="
|
||||
[mod."golang.org/x/crypto"]
|
||||
version = "v0.41.0"
|
||||
hash = "sha256-o5Di0lsFmYnXl7a5MBTqmN9vXMCRpE9ay71C1Ar8jEY="
|
||||
version = "v0.45.0"
|
||||
hash = "sha256-IpNesJYxFcs2jGvagwJrUD/gsJfA3UiETjQwYByXxSY="
|
||||
[mod."golang.org/x/exp"]
|
||||
version = "v0.0.0-20250531010427-b6e5de432a8b"
|
||||
hash = "sha256-QaFfjyB+pogCkUkJskR9xnXwkCOU828XJRrzwwLm6Ms="
|
||||
[mod."golang.org/x/net"]
|
||||
version = "v0.43.0"
|
||||
hash = "sha256-bf3iQFrsC8BoarVaS0uSspEFAcr1zHp1uziTtBpwV34="
|
||||
version = "v0.47.0"
|
||||
hash = "sha256-2qFgCd0YfNCGkLrf+xvnhQtKjSe8CymMdLlN3svUYTg="
|
||||
[mod."golang.org/x/oauth2"]
|
||||
version = "v0.30.0"
|
||||
hash = "sha256-btD7BUtQpOswusZY5qIU90uDo38buVrQ0tmmQ8qNHDg="
|
||||
[mod."golang.org/x/sync"]
|
||||
version = "v0.16.0"
|
||||
hash = "sha256-sqKDRESeMzLe0jWGWltLZL/JIgrn0XaIeBWCzVN3Bks="
|
||||
version = "v0.18.0"
|
||||
hash = "sha256-S8o6y7GOaYWeq+TzT8BB6T+1mg82Mu08V0TL3ukJprg="
|
||||
[mod."golang.org/x/sys"]
|
||||
version = "v0.35.0"
|
||||
hash = "sha256-ZKM8pesQE6NAFZeKQ84oPn5JMhGr8g4TSwLYAsHMGSI="
|
||||
version = "v0.38.0"
|
||||
hash = "sha256-1+i5EaG3JwH3KMtefzJLG5R6jbOeJM4GK3/LHBVnSy0="
|
||||
[mod."golang.org/x/text"]
|
||||
version = "v0.28.0"
|
||||
hash = "sha256-8UlJniGK+km4Hmrw6XMxELnExgrih7+z8tU26Cntmto="
|
||||
version = "v0.31.0"
|
||||
hash = "sha256-AT46RrSmV6+/d5FDhs9fPwYzmQ7WSo+YL9tPfhREwLw="
|
||||
[mod."google.golang.org/api"]
|
||||
version = "v0.247.0"
|
||||
hash = "sha256-UzTtydHmNqh1OXbxcN5qNKQxb5dV6h2Mo6DH4P219Ec="
|
||||
|
||||
@@ -1 +1 @@
|
||||
"1.4.332"
|
||||
"1.4.349"
|
||||
|
||||
@@ -3,6 +3,7 @@
|
||||
"""Extracts pattern information from the ~/.config/fabric/patterns directory,
|
||||
creates JSON files for pattern extracts and descriptions, and updates web static files.
|
||||
"""
|
||||
|
||||
import os
|
||||
import json
|
||||
import shutil
|
||||
@@ -33,7 +34,13 @@ def get_pattern_extract(pattern_path):
|
||||
def extract_pattern_info():
|
||||
"""Extract pattern information from the patterns directory"""
|
||||
script_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
patterns_dir = os.path.expanduser("~/.config/fabric/patterns")
|
||||
local_patterns_dir = os.path.join(script_dir, "..", "..", "data", "patterns")
|
||||
|
||||
if os.path.exists(local_patterns_dir):
|
||||
patterns_dir = local_patterns_dir
|
||||
else:
|
||||
patterns_dir = os.path.expanduser("~/.config/fabric/patterns")
|
||||
|
||||
print(f"\nScanning patterns directory: {patterns_dir}")
|
||||
|
||||
extracts_path = os.path.join(script_dir, "pattern_extracts.json")
|
||||
|
||||
@@ -1924,6 +1924,14 @@
|
||||
"tags": [
|
||||
"VISUALIZE"
|
||||
]
|
||||
},
|
||||
{
|
||||
"patternName": "concall_summary",
|
||||
"description": "Extract strategic insights from earnings transcripts for investors.",
|
||||
"tags": [
|
||||
"SUMMARIZE",
|
||||
"BUSINESS"
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -931,6 +931,10 @@
|
||||
{
|
||||
"patternName": "create_conceptmap",
|
||||
"pattern_extract": "--- ### IDENTITY AND PURPOSE You are an intelligent assistant specialized in **knowledge visualization and educational data structuring**. You are capable of reading unstructured textual content (.txt or .md files), extracting **main concepts, subthemes, and logical relationships**, and transforming them into a **fully interactive conceptual map** built in **HTML using Vis.js (vis-network)**. You understand hierarchical, causal, and correlative relations between ideas and express them through **nodes and directed edges**. You ensure that the resulting HTML file is **autonomous, interactive, and visually consistent** with the Vis.js framework. You are precise, systematic, and maintain semantic coherence between concepts and their relationships. You automatically name the output file according to the **detected topic**, ensuring compatibility and clarity (e.g., `map_hist_china.html`). --- ### TASK You are given a `.txt` or `.md` file containing explanatory, conceptual, or thematic content. Your task is to: 1. **Extract** the main concepts and secondary ideas. 2. **Identify logical or hierarchical relationships** among these concepts using concise action verbs. 3. **Structure the output** as a self-contained, interactive HTML document that visually represents these relationships using the **Vis.js (vis-network)** library. The goal is to generate a **fully functional conceptual map** that can be opened directly in a browser without external dependencies. --- ### ACTIONS 1. **Analyze and Extract Concepts** - Read and process the uploaded `.txt` or `.md` file. - Identify main themes, subthemes, and key terms. - Convert each key concept into a node. 2. **Map Relationships** - Detect logical and hierarchical relations between concepts. - Use short, descriptive verbs such as: \"causes\", \"contributes to\", \"depends on\", \"evolves into\", \"results in\", \"influences\", \"generates\" / \"creates\", \"culminates in. 3. **Generate Node Structure** ```json {\"id\": \"conceito_id\", \"label\": \"Conceito\", \"title\": \"<b>Concept:</b> Conceito<br><i>Drag to position, double-click to release.</i>\"} ``` 4. **Generate Edge Structure** ```json {\"from\": \"conceito_origem\", \"to\": \"conceito_destino\", \"label\": \"verbo\", \"title\": \"<b>Relationship:</b> verbo\"} ``` 5. **Apply Visual and Physical Configuration** ```js shape: \"dot\", color: { border: \"#4285F4\", background: \"#ffffff\", highlight: { border: \"#34A853\", background: \"#e6f4ea\" } }, font: { size: 14, color: \"#3c4043\" }, borderWidth: 2, size: 20 // Edges color: { color: \"#dee2e6\", highlight: \"#34A853\" }, arrows: { to: { enabled: true, scaleFactor: 0.7 } }, font: { align: \"middle\", size: 12, color: \"#5f6368\" }, width: 2 // Physics physics: { solver: \"forceAtlas2Based\", forceAtlas2Based: { gravitationalConstant: -50, centralGravity: 0.005, springLength: 100, springConstant: 0.18 }, maxVelocity: 146, minVelocity: 0.1, stabilization: { iterations: 150 } } ``` 6. **Implement Interactivity** ```js // Fix node on drag end network.on(\"dragEnd\", (params) => { if (params.nodes.length > 0) { nodes.update({ id: params.nodes[0], fixed: true }); } }); // Release node on double click network.on(\"doubleClick\", (params) => { if (params.nodes.length > 0) { nodes.update({ id: params.nodes[0], fixed: false }); } }); ``` 7. **Assemble the Complete HTML Structure** ```html <head> <title>Mapa Conceitual — [TEMA DETECTADO DO ARQUIVO]</title> <script src=\"https://unpkg.com/vis-network/standalone/umd/vis-network.min.js\"></script> <link href=\"https://unpkg.com/vis-network/styles/vis-network.min.css\" rel=\"stylesheet\" /> </head> <body> <div id=\"map\"></div> <script type=\"text/javascript\"> // nodes, edges, options, and interactive network initialization </script> </body> ``` 8. **Auto-name Output File** Automatically save the generated HTML file based on the detected topic: ``` mapa_[tema_detectado].html ``` --- ###"
|
||||
},
|
||||
{
|
||||
"patternName": "concall_summary",
|
||||
"pattern_extract": "# IDENTITY and PURPOSE You are an equity research analyst specializing in earnings and conference call analysis. Your role involves carefully examining transcripts to extract actionable insights that can inform investment decisions. You need to focus on several key areas, including management commentary, analyst questions, financial and operational insights, risks and red flags, hidden signals, and an executive summary. Your task is to distill complex information into clear, concise bullet points, capturing strategic themes, growth drivers, and potential concerns. It is crucial to interpret the tone, identify contradictions, and highlight any subtle cues that may indicate future strategic shifts or risks. Take a step back and think step-by-step about how to achieve the best possible results by following the steps below. # STEPS * Analyze the transcript to extract management commentary, focusing on strategic themes, growth drivers, margin commentary, guidance, tone analysis, and any contradictions or vague areas. * Extract a summary of the content in exactly **25 words**, including who is presenting and the content being discussed; place this under a **SUMMARY** section. * For each analyst's question, determine the underlying concern, summarize management’s exact answer, evaluate if the answers address the question fully, and identify anything the management avoided or deflected. * Gather financial and operational insights, including commentary on demand, pricing, capacity, market share, cost inflation, raw material trends, and supply-chain issues. * Identify risks and red flags by noting any negative commentary, early warning signs, unusual wording, delayed responses, repeated disclaimers, and areas where management seemed less confident. * Detect hidden signals such as forward-looking hints, unasked but important questions, and subtle cues about strategy shifts or stress. * Create an executive summary in bullet points, listing the 10 most important takeaways, 3 surprises, and 3 things to track in the next quarter. # OUTPUT STRUCTURE * MANAGEMENT COMMENTARY * Key strategic themes * Growth drivers discussed * Margin commentary * Guidance (explicit + implicit) * Tone analysis (positive/neutral/negative) * Any contradictions or vague areas * ANALYST QUESTIONS (Q&A) * For each analyst (use bullets, one analyst per bullet-group): * Underlying concern (what the question REALLY asked) * Management’s exact answer (concise) * Answer completeness (Yes/No — short explanation) * Items management avoided or deflected * FINANCIAL & OPERATIONAL INSIGHTS * Demand, pricing, capacity, market share commentary * Cost inflation, raw material trends, supply-chain issues * Segment-wise performance and commentary (if applicable) * RISKS & RED FLAGS * Negative commentary or early-warning signs * Unusual wording, delayed responses, repeated disclaimers * Areas where management was less confident * HIDDEN SIGNALS * Forward-looking hints and tone shifts * Important topics not asked by analysts but relevant * Subtle cues of strategy change, stress, or opportunity * EXECUTIVE SUMMARY * 10 most important takeaways (bullet points) * 3 surprises (bullet points) * 3 things to track next quarter (bullet points) * SUMMARY (exactly 25 words) * A single 25-word sentence summarizing who presented and what was discussed # OUTPUT INSTRUCTIONS * Only output Markdown. * Provide everything in"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -26,9 +26,9 @@
|
||||
"eslint-plugin-svelte": "^2.46.1",
|
||||
"lucide-svelte": "^0.309.0",
|
||||
"mdsvex": "^0.11.2",
|
||||
"patch-package": "^8.0.0",
|
||||
"patch-package": "^8.0.1",
|
||||
"pdf-to-markdown-core": "github:jzillmann/pdf-to-markdown#modularize",
|
||||
"pdfjs-dist": "^4.2.67",
|
||||
"pdfjs-dist": "^5.4.449",
|
||||
"postcss": "^8.5.3",
|
||||
"postcss-load-config": "^6.0.1",
|
||||
"rehype-autolink-headings": "^7.1.0",
|
||||
|
||||
565
web/pnpm-lock.yaml
generated
565
web/pnpm-lock.yaml
generated
File diff suppressed because it is too large
Load Diff
@@ -1,239 +1,284 @@
|
||||
import { get } from "svelte/store";
|
||||
import type {
|
||||
ChatRequest,
|
||||
StreamResponse,
|
||||
ChatError as IChatError,
|
||||
ChatPrompt
|
||||
} from '$lib/interfaces/chat-interface';
|
||||
import { get } from 'svelte/store';
|
||||
import { modelConfig } from '$lib/store/model-store';
|
||||
import { systemPrompt, selectedPatternName, patternVariables } from '$lib/store/pattern-store';
|
||||
import { chatConfig } from '$lib/store/chat-config';
|
||||
import { messageStore } from '$lib/store/chat-store';
|
||||
import { languageStore } from '$lib/store/language-store';
|
||||
import { selectedStrategy } from '$lib/store/strategy-store';
|
||||
ChatPrompt,
|
||||
ChatRequest,
|
||||
ChatError as IChatError,
|
||||
StreamResponse,
|
||||
} from "$lib/interfaces/chat-interface";
|
||||
import { chatConfig } from "$lib/store/chat-config";
|
||||
import { languageStore } from "$lib/store/language-store";
|
||||
import { modelConfig } from "$lib/store/model-store";
|
||||
import {
|
||||
patternVariables,
|
||||
selectedPatternName,
|
||||
systemPrompt,
|
||||
} from "$lib/store/pattern-store";
|
||||
import { selectedStrategy } from "$lib/store/strategy-store";
|
||||
|
||||
class LanguageValidator {
|
||||
constructor(private targetLanguage: string) {}
|
||||
constructor(private targetLanguage: string) {}
|
||||
|
||||
enforceLanguage(content: string): string {
|
||||
if (this.targetLanguage === 'en') return content;
|
||||
return `[Language: ${this.targetLanguage}]\n${content}`;
|
||||
}
|
||||
enforceLanguage(content: string): string {
|
||||
if (this.targetLanguage === "en") return content;
|
||||
return `[Language: ${this.targetLanguage}]\n${content}`;
|
||||
}
|
||||
}
|
||||
|
||||
export class ChatError extends Error implements IChatError {
|
||||
constructor(
|
||||
message: string,
|
||||
public readonly code: string = 'CHAT_ERROR',
|
||||
public readonly details?: unknown
|
||||
) {
|
||||
super(message);
|
||||
this.name = 'ChatError';
|
||||
}
|
||||
constructor(
|
||||
message: string,
|
||||
public readonly code: string = "CHAT_ERROR",
|
||||
public readonly details?: unknown,
|
||||
) {
|
||||
super(message);
|
||||
this.name = "ChatError";
|
||||
}
|
||||
}
|
||||
|
||||
export class ChatService {
|
||||
private validator: LanguageValidator;
|
||||
private validator: LanguageValidator;
|
||||
|
||||
constructor() {
|
||||
this.validator = new LanguageValidator(get(languageStore));
|
||||
}
|
||||
constructor() {
|
||||
this.validator = new LanguageValidator(get(languageStore));
|
||||
}
|
||||
|
||||
private async fetchStream(request: ChatRequest): Promise<ReadableStream<StreamResponse>> {
|
||||
try {
|
||||
console.log('\n=== ChatService Request Start ===');
|
||||
console.log('1. Request details:', {
|
||||
language: get(languageStore),
|
||||
pattern: get(selectedPatternName),
|
||||
promptCount: request.prompts?.length,
|
||||
messageCount: request.messages?.length
|
||||
});
|
||||
// NEW: Log the full payload before sending to backend
|
||||
console.log('Final ChatRequest payload:', JSON.stringify(request, null, 2));
|
||||
private async fetchStream(
|
||||
request: ChatRequest,
|
||||
): Promise<ReadableStream<StreamResponse>> {
|
||||
try {
|
||||
console.log("\n=== ChatService Request Start ===");
|
||||
console.log("1. Request details:", {
|
||||
language: get(languageStore),
|
||||
pattern: get(selectedPatternName),
|
||||
promptCount: request.prompts?.length,
|
||||
messageCount: request.messages?.length,
|
||||
});
|
||||
// NEW: Log the full payload before sending to backend
|
||||
console.log(
|
||||
"Final ChatRequest payload:",
|
||||
JSON.stringify(request, null, 2),
|
||||
);
|
||||
|
||||
const response = await fetch('/api/chat', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(request),
|
||||
});
|
||||
const response = await fetch("/api/chat", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify(request),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new ChatError(`HTTP error! status: ${response.status}`, 'HTTP_ERROR', { status: response.status });
|
||||
}
|
||||
if (!response.ok) {
|
||||
throw new ChatError(
|
||||
`HTTP error! status: ${response.status}`,
|
||||
"HTTP_ERROR",
|
||||
{ status: response.status },
|
||||
);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new ChatError('Response body is null', 'NULL_RESPONSE');
|
||||
}
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new ChatError("Response body is null", "NULL_RESPONSE");
|
||||
}
|
||||
|
||||
return this.createMessageStream(reader);
|
||||
} catch (error) {
|
||||
if (error instanceof ChatError) throw error;
|
||||
throw new ChatError('Failed to fetch chat stream', 'FETCH_ERROR', error);
|
||||
}
|
||||
}
|
||||
return this.createMessageStream(reader);
|
||||
} catch (error) {
|
||||
if (error instanceof ChatError) throw error;
|
||||
throw new ChatError("Failed to fetch chat stream", "FETCH_ERROR", error);
|
||||
}
|
||||
}
|
||||
|
||||
private cleanPatternOutput(content: string): string {
|
||||
// Remove markdown fence if present
|
||||
let cleaned = content.replace(/^```markdown\n/, '');
|
||||
cleaned = cleaned.replace(/\n```$/, '');
|
||||
private cleanPatternOutput(content: string): string {
|
||||
// Remove markdown fence if present
|
||||
let cleaned = content.replace(/^```markdown\n/, "");
|
||||
cleaned = cleaned.replace(/\n```$/, "");
|
||||
|
||||
// Existing cleaning
|
||||
cleaned = cleaned.replace(/^# OUTPUT\s*\n/, '');
|
||||
cleaned = cleaned.replace(/^\s*\n/, '');
|
||||
cleaned = cleaned.replace(/\n\s*$/, '');
|
||||
cleaned = cleaned.replace(/^#\s+([A-Z]+):/gm, '$1:');
|
||||
cleaned = cleaned.replace(/^#\s+([A-Z]+)\s*$/gm, '$1');
|
||||
cleaned = cleaned.trim();
|
||||
cleaned = cleaned.replace(/\n{3,}/g, '\n\n');
|
||||
return cleaned;
|
||||
}
|
||||
// Existing cleaning
|
||||
cleaned = cleaned.replace(/^# OUTPUT\s*\n/, "");
|
||||
cleaned = cleaned.replace(/^\s*\n/, "");
|
||||
cleaned = cleaned.replace(/\n\s*$/, "");
|
||||
cleaned = cleaned.replace(/^#\s+([A-Z]+):/gm, "$1:");
|
||||
cleaned = cleaned.replace(/^#\s+([A-Z]+)\s*$/gm, "$1");
|
||||
cleaned = cleaned.trim();
|
||||
cleaned = cleaned.replace(/\n{3,}/g, "\n\n");
|
||||
return cleaned;
|
||||
}
|
||||
|
||||
private createMessageStream(reader: ReadableStreamDefaultReader<Uint8Array>): ReadableStream<StreamResponse> {
|
||||
let buffer = '';
|
||||
const cleanPatternOutput = this.cleanPatternOutput.bind(this);
|
||||
const language = get(languageStore);
|
||||
const validator = new LanguageValidator(language);
|
||||
private createMessageStream(
|
||||
reader: ReadableStreamDefaultReader<Uint8Array>,
|
||||
): ReadableStream<StreamResponse> {
|
||||
let buffer = "";
|
||||
const cleanPatternOutput = this.cleanPatternOutput.bind(this);
|
||||
const language = get(languageStore);
|
||||
const validator = new LanguageValidator(language);
|
||||
|
||||
const processResponse = (response: StreamResponse) => {
|
||||
const pattern = get(selectedPatternName);
|
||||
const processResponse = (response: StreamResponse) => {
|
||||
const pattern = get(selectedPatternName);
|
||||
|
||||
if (pattern) {
|
||||
response.content = cleanPatternOutput(response.content);
|
||||
// Simplified format determination - always markdown unless mermaid
|
||||
const isMermaid = [
|
||||
'graph TD', 'gantt', 'flowchart',
|
||||
'sequenceDiagram', 'classDiagram', 'stateDiagram'
|
||||
].some(starter => response.content.trim().startsWith(starter));
|
||||
if (pattern) {
|
||||
response.content = cleanPatternOutput(response.content);
|
||||
// Simplified format determination - always markdown unless mermaid
|
||||
const isMermaid = [
|
||||
"graph TD",
|
||||
"gantt",
|
||||
"flowchart",
|
||||
"sequenceDiagram",
|
||||
"classDiagram",
|
||||
"stateDiagram",
|
||||
].some((starter) => response.content.trim().startsWith(starter));
|
||||
|
||||
response.format = isMermaid ? 'mermaid' : 'markdown';
|
||||
}
|
||||
response.format = isMermaid ? "mermaid" : "markdown";
|
||||
}
|
||||
|
||||
if (response.type === 'content') {
|
||||
response.content = validator.enforceLanguage(response.content);
|
||||
}
|
||||
if (response.type === "content") {
|
||||
response.content = validator.enforceLanguage(response.content);
|
||||
}
|
||||
|
||||
return response;
|
||||
};
|
||||
return new ReadableStream({
|
||||
async start(controller) {
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
return response;
|
||||
};
|
||||
return new ReadableStream({
|
||||
async start(controller) {
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
buffer += new TextDecoder().decode(value);
|
||||
const messages = buffer.split('\n\n').filter(msg => msg.startsWith('data: '));
|
||||
buffer += new TextDecoder().decode(value);
|
||||
const messages = buffer
|
||||
.split("\n\n")
|
||||
.filter((msg) => msg.startsWith("data: "));
|
||||
|
||||
if (messages.length > 1) {
|
||||
buffer = messages.pop() || '';
|
||||
for (const msg of messages) {
|
||||
try {
|
||||
let response = JSON.parse(msg.slice(6)) as StreamResponse;
|
||||
response = processResponse(response);
|
||||
controller.enqueue(response);
|
||||
} catch (parseError) {
|
||||
console.error('Error parsing stream message:', parseError);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
if (messages.length > 1) {
|
||||
buffer = messages.pop() || "";
|
||||
for (const msg of messages) {
|
||||
try {
|
||||
let response = JSON.parse(msg.slice(6)) as StreamResponse;
|
||||
response = processResponse(response);
|
||||
controller.enqueue(response);
|
||||
} catch (parseError) {
|
||||
console.error("Error parsing stream message:", parseError);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (buffer.startsWith('data: ')) {
|
||||
try {
|
||||
let response = JSON.parse(buffer.slice(6)) as StreamResponse;
|
||||
response = processResponse(response);
|
||||
controller.enqueue(response);
|
||||
} catch (parseError) {
|
||||
console.error('Error parsing final message:', parseError);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
controller.error(new ChatError('Stream processing error', 'STREAM_ERROR', error));
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
controller.close();
|
||||
}
|
||||
},
|
||||
cancel() {
|
||||
reader.cancel();
|
||||
}
|
||||
});
|
||||
}
|
||||
if (buffer.startsWith("data: ")) {
|
||||
try {
|
||||
let response = JSON.parse(buffer.slice(6)) as StreamResponse;
|
||||
response = processResponse(response);
|
||||
controller.enqueue(response);
|
||||
} catch (parseError) {
|
||||
console.error("Error parsing final message:", parseError);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
controller.error(
|
||||
new ChatError("Stream processing error", "STREAM_ERROR", error),
|
||||
);
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
controller.close();
|
||||
}
|
||||
},
|
||||
cancel() {
|
||||
reader.cancel();
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
private createChatPrompt(userInput: string, systemPromptText?: string): ChatPrompt {
|
||||
const config = get(modelConfig);
|
||||
const language = get(languageStore);
|
||||
private createChatPrompt(
|
||||
userInput: string,
|
||||
systemPromptText?: string,
|
||||
): ChatPrompt {
|
||||
const config = get(modelConfig);
|
||||
const language = get(languageStore);
|
||||
|
||||
const languageInstruction = language !== 'en'
|
||||
? `You MUST respond in ${language} language. All output must be in ${language}. `
|
||||
// ? `You MUST respond in ${language} language. ALL output, including section headers, titles, and formatting, MUST be translated into ${language}. It is CRITICAL that you translate ALL headers, such as SUMMARY, IDEAS, QUOTES, TAKEAWAYS, MAIN POINTS, etc., into ${language}. Maintain markdown formatting in the response. Do not output any English headers.`
|
||||
: '';
|
||||
const languageInstruction =
|
||||
language !== "en"
|
||||
? `You MUST respond in ${language} language. All output must be in ${language}. `
|
||||
: // ? `You MUST respond in ${language} language. ALL output, including section headers, titles, and formatting, MUST be translated into ${language}. It is CRITICAL that you translate ALL headers, such as SUMMARY, IDEAS, QUOTES, TAKEAWAYS, MAIN POINTS, etc., into ${language}. Maintain markdown formatting in the response. Do not output any English headers.`
|
||||
"";
|
||||
|
||||
const finalSystemPrompt = languageInstruction + (systemPromptText ?? get(systemPrompt));
|
||||
const finalSystemPrompt =
|
||||
languageInstruction + (systemPromptText ?? get(systemPrompt));
|
||||
|
||||
const finalUserInput = language !== 'en'
|
||||
? `${userInput}\n\nIMPORTANT: Respond in ${language} language only.`
|
||||
: userInput;
|
||||
const finalUserInput =
|
||||
language !== "en"
|
||||
? `${userInput}\n\nIMPORTANT: Respond in ${language} language only.`
|
||||
: userInput;
|
||||
|
||||
return {
|
||||
userInput: finalUserInput,
|
||||
systemPrompt: finalSystemPrompt,
|
||||
model: config.model,
|
||||
patternName: get(selectedPatternName),
|
||||
strategyName: get(selectedStrategy), // Add selected strategy to prompt
|
||||
variables: get(patternVariables) // Add pattern variables
|
||||
};
|
||||
}
|
||||
|
||||
public async createChatRequest(userInput: string, systemPromptText?: string, isPattern: boolean = false): Promise<ChatRequest> {
|
||||
const prompt = this.createChatPrompt(userInput, systemPromptText);
|
||||
const config = get(chatConfig);
|
||||
const language = get(languageStore);
|
||||
|
||||
return {
|
||||
prompts: [prompt],
|
||||
messages: [],
|
||||
language: language, // Add language at the top level for backend compatibility
|
||||
...config
|
||||
};
|
||||
}
|
||||
|
||||
public async streamPattern(userInput: string, systemPromptText?: string): Promise<ReadableStream<StreamResponse>> {
|
||||
const request = await this.createChatRequest(userInput, systemPromptText, true);
|
||||
return this.fetchStream(request);
|
||||
}
|
||||
|
||||
public async streamChat(userInput: string, systemPromptText?: string): Promise<ReadableStream<StreamResponse>> {
|
||||
const request = await this.createChatRequest(userInput, systemPromptText);
|
||||
return this.fetchStream(request);
|
||||
}
|
||||
|
||||
public async processStream(
|
||||
stream: ReadableStream<StreamResponse>,
|
||||
onContent: (content: string, response?: StreamResponse) => void,
|
||||
onError: (error: Error) => void
|
||||
): Promise<void> {
|
||||
const reader = stream.getReader();
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
if (value.type === 'error') {
|
||||
throw new ChatError(value.content, 'STREAM_CONTENT_ERROR');
|
||||
}
|
||||
|
||||
if (value.type === 'content') {
|
||||
onContent(value.content, value);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
onError(error instanceof ChatError ? error : new ChatError('Stream processing error', 'STREAM_ERROR', error));
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
|
||||
}
|
||||
}
|
||||
return {
|
||||
userInput: finalUserInput,
|
||||
systemPrompt: finalSystemPrompt,
|
||||
model: config.model,
|
||||
patternName: get(selectedPatternName),
|
||||
strategyName: get(selectedStrategy), // Add selected strategy to prompt
|
||||
variables: get(patternVariables), // Add pattern variables
|
||||
};
|
||||
}
|
||||
|
||||
public async createChatRequest(
|
||||
userInput: string,
|
||||
systemPromptText?: string,
|
||||
isPattern: boolean = false,
|
||||
): Promise<ChatRequest> {
|
||||
const prompt = this.createChatPrompt(userInput, systemPromptText);
|
||||
const config = get(chatConfig);
|
||||
const language = get(languageStore);
|
||||
|
||||
return {
|
||||
prompts: [prompt],
|
||||
messages: [],
|
||||
language: language, // Add language at the top level for backend compatibility
|
||||
...config,
|
||||
};
|
||||
}
|
||||
|
||||
public async streamPattern(
|
||||
userInput: string,
|
||||
systemPromptText?: string,
|
||||
): Promise<ReadableStream<StreamResponse>> {
|
||||
const request = await this.createChatRequest(
|
||||
userInput,
|
||||
systemPromptText,
|
||||
true,
|
||||
);
|
||||
return this.fetchStream(request);
|
||||
}
|
||||
|
||||
public async streamChat(
|
||||
userInput: string,
|
||||
systemPromptText?: string,
|
||||
): Promise<ReadableStream<StreamResponse>> {
|
||||
const request = await this.createChatRequest(userInput, systemPromptText);
|
||||
return this.fetchStream(request);
|
||||
}
|
||||
|
||||
public async processStream(
|
||||
stream: ReadableStream<StreamResponse>,
|
||||
onContent: (content: string, response?: StreamResponse) => void,
|
||||
onError: (error: Error) => void,
|
||||
): Promise<void> {
|
||||
const reader = stream.getReader();
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
if (value.type === "error") {
|
||||
throw new ChatError(value.content, "STREAM_CONTENT_ERROR");
|
||||
}
|
||||
|
||||
if (value.type === "content") {
|
||||
onContent(value.content, value);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
onError(
|
||||
error instanceof ChatError
|
||||
? error
|
||||
: new ChatError("Stream processing error", "STREAM_ERROR", error),
|
||||
);
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,78 +1,74 @@
|
||||
import { createPipeline, transformers } from 'pdf-to-markdown-core/lib/src';
|
||||
import { PARSE_SCHEMA } from 'pdf-to-markdown-core/lib/src/PdfParser';
|
||||
import * as pdfjs from 'pdfjs-dist';
|
||||
import pdfConfig from './pdf-config';
|
||||
import { createPipeline, transformers } from "pdf-to-markdown-core/lib/src";
|
||||
import { PARSE_SCHEMA } from "pdf-to-markdown-core/lib/src/PdfParser";
|
||||
|
||||
// pdfjs-dist v5+ requires browser APIs at import time, so we use dynamic imports
|
||||
let pdfjs: typeof import("pdfjs-dist") | null = null;
|
||||
|
||||
export class PdfConversionService {
|
||||
constructor() {
|
||||
if (typeof window !== 'undefined') {
|
||||
console.log('PDF.js version:', pdfjs.version);
|
||||
// Initialize PDF.js configuration from the shared config
|
||||
pdfConfig.initialize();
|
||||
console.log('Worker configuration complete');
|
||||
}
|
||||
}
|
||||
private async ensureInitialized(): Promise<typeof import("pdfjs-dist")> {
|
||||
if (!pdfjs) {
|
||||
// Dynamic import to avoid SSR issues with pdfjs-dist v5+
|
||||
pdfjs = await import("pdfjs-dist");
|
||||
const pdfConfig = (await import("./pdf-config")).default;
|
||||
console.log("PDF.js version:", pdfjs.version);
|
||||
await pdfConfig.initialize();
|
||||
console.log("Worker configuration complete");
|
||||
}
|
||||
return pdfjs;
|
||||
}
|
||||
|
||||
async convertToMarkdown(file: File): Promise<string> {
|
||||
console.log('Starting PDF conversion:', {
|
||||
fileName: file.name,
|
||||
fileSize: file.size
|
||||
});
|
||||
async convertToMarkdown(file: File): Promise<string> {
|
||||
console.log("Starting PDF conversion:", {
|
||||
fileName: file.name,
|
||||
fileSize: file.size,
|
||||
});
|
||||
|
||||
const buffer = await file.arrayBuffer();
|
||||
console.log('Buffer created:', buffer.byteLength);
|
||||
const pdfjsLib = await this.ensureInitialized();
|
||||
|
||||
const pipeline = createPipeline(pdfjs, {
|
||||
transformConfig: {
|
||||
transformers
|
||||
}
|
||||
});
|
||||
console.log('Pipeline created');
|
||||
const buffer = await file.arrayBuffer();
|
||||
console.log("Buffer created:", buffer.byteLength);
|
||||
|
||||
const result = await pipeline.parse(
|
||||
buffer,
|
||||
(progress) => console.log('Processing:', {
|
||||
stage: progress.stages,
|
||||
details: progress.stageDetails,
|
||||
progress: progress.stageProgress
|
||||
})
|
||||
);
|
||||
console.log('Parse complete, validating result');
|
||||
const pipeline = createPipeline(pdfjsLib, {
|
||||
transformConfig: {
|
||||
transformers,
|
||||
},
|
||||
});
|
||||
console.log("Pipeline created");
|
||||
|
||||
const transformed = result.transform();
|
||||
console.log('Transform applied:', transformed);
|
||||
const result = await pipeline.parse(buffer, (progress) =>
|
||||
console.log("Processing:", {
|
||||
stage: progress.stages,
|
||||
details: progress.stageDetails,
|
||||
progress: progress.stageProgress,
|
||||
}),
|
||||
);
|
||||
console.log("Parse complete, validating result");
|
||||
|
||||
const markdown = transformed.convert({
|
||||
convert: (items) => {
|
||||
console.log('PDF Structure:', {
|
||||
itemCount: items.length,
|
||||
firstItem: items[0],
|
||||
schema: PARSE_SCHEMA // ['transform', 'width', 'height', 'str', 'fontName', 'dir']
|
||||
});
|
||||
|
||||
const text = items
|
||||
.map(item => item.value('str')) // Using 'str' instead of 'text' based on PARSE_SCHEMA
|
||||
.filter(Boolean)
|
||||
.join('\n');
|
||||
|
||||
console.log('Converted text:', {
|
||||
length: text.length,
|
||||
preview: text.substring(0, 100)
|
||||
});
|
||||
|
||||
return text;
|
||||
}
|
||||
});
|
||||
|
||||
const transformed = result.transform();
|
||||
console.log("Transform applied:", transformed);
|
||||
|
||||
return markdown;
|
||||
}
|
||||
const markdown = transformed.convert({
|
||||
convert: (items) => {
|
||||
console.log("PDF Structure:", {
|
||||
itemCount: items.length,
|
||||
firstItem: items[0],
|
||||
schema: PARSE_SCHEMA, // ['transform', 'width', 'height', 'str', 'fontName', 'dir']
|
||||
});
|
||||
|
||||
const text = items
|
||||
.map((item) => item.value("str")) // Using 'str' instead of 'text' based on PARSE_SCHEMA
|
||||
.filter(Boolean)
|
||||
.join("\n");
|
||||
|
||||
console.log("Converted text:", {
|
||||
length: text.length,
|
||||
preview: text.substring(0, 100),
|
||||
});
|
||||
|
||||
return text;
|
||||
},
|
||||
});
|
||||
|
||||
return markdown;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -1,20 +1,19 @@
|
||||
import { browser } from '$app/environment';
|
||||
import { GlobalWorkerOptions } from 'pdfjs-dist';
|
||||
import { browser } from "$app/environment";
|
||||
|
||||
// Set up the worker source location - point to static file in public directory
|
||||
const workerSrc = '/pdf.worker.min.mjs';
|
||||
|
||||
// Configure the worker options only on the client side
|
||||
if (browser) {
|
||||
GlobalWorkerOptions.workerSrc = workerSrc;
|
||||
}
|
||||
|
||||
// Export the configuration
|
||||
// Export the configuration - accepts pdfjs module to avoid top-level import
|
||||
// This is necessary because pdfjs-dist v5+ uses browser APIs at import time
|
||||
export default {
|
||||
initialize: () => {
|
||||
if (browser) {
|
||||
console.log('PDF.js worker initialized at', workerSrc);
|
||||
}
|
||||
}
|
||||
};
|
||||
initialize: async () => {
|
||||
if (browser) {
|
||||
// Dynamic import to avoid SSR issues
|
||||
const pdfjs = await import("pdfjs-dist");
|
||||
const { GlobalWorkerOptions, version } = pdfjs;
|
||||
|
||||
// Use CDN-hosted worker to avoid bundling third-party minified code in the repo
|
||||
const workerSrc = `https://unpkg.com/pdfjs-dist@${version}/build/pdf.worker.min.mjs`;
|
||||
GlobalWorkerOptions.workerSrc = workerSrc;
|
||||
|
||||
console.log(`PDF.js worker v${version} initialized from CDN`);
|
||||
}
|
||||
},
|
||||
};
|
||||
|
||||
@@ -1,19 +1,24 @@
|
||||
import { writable, derived, get } from 'svelte/store';
|
||||
import type { ChatState, Message, StreamResponse } from '$lib/interfaces/chat-interface';
|
||||
import { ChatService, ChatError } from '$lib/services/ChatService';
|
||||
import { languageStore } from '$lib/store/language-store';
|
||||
import { selectedPatternName } from '$lib/store/pattern-store';
|
||||
import { derived, get, writable } from "svelte/store";
|
||||
import { browser } from "$app/environment";
|
||||
import type {
|
||||
ChatState,
|
||||
Message,
|
||||
StreamResponse,
|
||||
} from "$lib/interfaces/chat-interface";
|
||||
import { ChatError, ChatService } from "$lib/services/ChatService";
|
||||
import { languageStore } from "$lib/store/language-store";
|
||||
import { selectedPatternName } from "$lib/store/pattern-store";
|
||||
|
||||
// Initialize chat service
|
||||
const chatService = new ChatService();
|
||||
|
||||
// Local storage key for persisting messages
|
||||
const MESSAGES_STORAGE_KEY = 'chat_messages';
|
||||
const MESSAGES_STORAGE_KEY = "chat_messages";
|
||||
|
||||
// Load initial messages from local storage
|
||||
const initialMessages = typeof localStorage !== 'undefined'
|
||||
? JSON.parse(localStorage.getItem(MESSAGES_STORAGE_KEY) || '[]')
|
||||
: [];
|
||||
// Load initial messages from local storage (only in browser)
|
||||
const initialMessages = browser
|
||||
? JSON.parse(localStorage.getItem(MESSAGES_STORAGE_KEY) || "[]")
|
||||
: [];
|
||||
|
||||
// Separate stores for different concerns
|
||||
export const messageStore = writable<Message[]>(initialMessages);
|
||||
@@ -21,134 +26,144 @@ export const streamingStore = writable<boolean>(false);
|
||||
export const errorStore = writable<string | null>(null);
|
||||
export const currentSession = writable<string | null>(null);
|
||||
|
||||
// Subscribe to messageStore changes to persist messages
|
||||
if (typeof localStorage !== 'undefined') {
|
||||
messageStore.subscribe($messages => {
|
||||
localStorage.setItem(MESSAGES_STORAGE_KEY, JSON.stringify($messages));
|
||||
});
|
||||
// Subscribe to messageStore changes to persist messages (only in browser)
|
||||
if (browser) {
|
||||
messageStore.subscribe(($messages) => {
|
||||
localStorage.setItem(MESSAGES_STORAGE_KEY, JSON.stringify($messages));
|
||||
});
|
||||
}
|
||||
|
||||
// Derived store for chat state
|
||||
export const chatState = derived(
|
||||
[messageStore, streamingStore],
|
||||
([$messages, $streaming]) => ({
|
||||
messages: $messages,
|
||||
isStreaming: $streaming
|
||||
})
|
||||
[messageStore, streamingStore],
|
||||
([$messages, $streaming]) => ({
|
||||
messages: $messages,
|
||||
isStreaming: $streaming,
|
||||
}),
|
||||
);
|
||||
|
||||
// Error handling utility
|
||||
function handleError(error: Error | string) {
|
||||
const errorMessage = error instanceof ChatError
|
||||
? `${error.code}: ${error.message}`
|
||||
: error instanceof Error
|
||||
? error.message
|
||||
: error;
|
||||
const errorMessage =
|
||||
error instanceof ChatError
|
||||
? `${error.code}: ${error.message}`
|
||||
: error instanceof Error
|
||||
? error.message
|
||||
: error;
|
||||
|
||||
errorStore.set(errorMessage);
|
||||
streamingStore.set(false);
|
||||
return errorMessage;
|
||||
errorStore.set(errorMessage);
|
||||
streamingStore.set(false);
|
||||
return errorMessage;
|
||||
}
|
||||
|
||||
export const setSession = (sessionName: string | null) => {
|
||||
currentSession.set(sessionName);
|
||||
if (!sessionName) {
|
||||
clearMessages();
|
||||
}
|
||||
currentSession.set(sessionName);
|
||||
if (!sessionName) {
|
||||
clearMessages();
|
||||
}
|
||||
};
|
||||
|
||||
export const clearMessages = () => {
|
||||
messageStore.set([]);
|
||||
errorStore.set(null);
|
||||
if (typeof localStorage !== 'undefined') {
|
||||
localStorage.removeItem(MESSAGES_STORAGE_KEY);
|
||||
}
|
||||
messageStore.set([]);
|
||||
errorStore.set(null);
|
||||
if (typeof localStorage !== "undefined") {
|
||||
localStorage.removeItem(MESSAGES_STORAGE_KEY);
|
||||
}
|
||||
};
|
||||
|
||||
export const revertLastMessage = () => {
|
||||
messageStore.update(messages => messages.slice(0, -1));
|
||||
messageStore.update((messages) => messages.slice(0, -1));
|
||||
};
|
||||
|
||||
export async function sendMessage(
|
||||
content: string,
|
||||
systemPromptText?: string,
|
||||
isSystem: boolean = false,
|
||||
) {
|
||||
try {
|
||||
console.log("\n=== Message Processing Start ===");
|
||||
console.log("1. Initial state:", {
|
||||
isSystem,
|
||||
hasSystemPrompt: !!systemPromptText,
|
||||
currentLanguage: get(languageStore),
|
||||
pattern: get(selectedPatternName),
|
||||
});
|
||||
|
||||
export async function sendMessage(content: string, systemPromptText?: string, isSystem: boolean = false) {
|
||||
try {
|
||||
console.log('\n=== Message Processing Start ===');
|
||||
console.log('1. Initial state:', {
|
||||
isSystem,
|
||||
hasSystemPrompt: !!systemPromptText,
|
||||
currentLanguage: get(languageStore),
|
||||
pattern: get(selectedPatternName)
|
||||
});
|
||||
const $streaming = get(streamingStore);
|
||||
if ($streaming) {
|
||||
throw new ChatError(
|
||||
"Message submission blocked - already streaming",
|
||||
"STREAMING_BLOCKED",
|
||||
);
|
||||
}
|
||||
|
||||
const $streaming = get(streamingStore);
|
||||
if ($streaming) {
|
||||
throw new ChatError('Message submission blocked - already streaming', 'STREAMING_BLOCKED');
|
||||
}
|
||||
streamingStore.set(true);
|
||||
errorStore.set(null);
|
||||
|
||||
streamingStore.set(true);
|
||||
errorStore.set(null);
|
||||
// Add message
|
||||
messageStore.update((messages) => [
|
||||
...messages,
|
||||
{
|
||||
role: isSystem ? "system" : "user",
|
||||
content,
|
||||
},
|
||||
]);
|
||||
|
||||
// Add message
|
||||
messageStore.update(messages => [...messages, {
|
||||
role: isSystem ? 'system' : 'user',
|
||||
content
|
||||
}]);
|
||||
console.log("2. Message added:", {
|
||||
role: isSystem ? "system" : "user",
|
||||
language: get(languageStore),
|
||||
});
|
||||
|
||||
console.log('2. Message added:', {
|
||||
role: isSystem ? 'system' : 'user',
|
||||
language: get(languageStore)
|
||||
});
|
||||
if (!isSystem) {
|
||||
console.log("3. Preparing chat stream:", {
|
||||
language: get(languageStore),
|
||||
pattern: get(selectedPatternName),
|
||||
hasSystemPrompt: !!systemPromptText,
|
||||
});
|
||||
|
||||
if (!isSystem) {
|
||||
console.log('3. Preparing chat stream:', {
|
||||
language: get(languageStore),
|
||||
pattern: get(selectedPatternName),
|
||||
hasSystemPrompt: !!systemPromptText
|
||||
});
|
||||
const stream = await chatService.streamChat(content, systemPromptText);
|
||||
console.log("4. Stream created");
|
||||
|
||||
const stream = await chatService.streamChat(content, systemPromptText);
|
||||
console.log('4. Stream created');
|
||||
await chatService.processStream(
|
||||
stream,
|
||||
(content: string, response?: StreamResponse) => {
|
||||
messageStore.update((messages) => {
|
||||
const newMessages = [...messages];
|
||||
const lastMessage = newMessages[newMessages.length - 1];
|
||||
|
||||
await chatService.processStream(
|
||||
stream,
|
||||
(content: string, response?: StreamResponse) => {
|
||||
messageStore.update(messages => {
|
||||
const newMessages = [...messages];
|
||||
const lastMessage = newMessages[newMessages.length - 1];
|
||||
if (lastMessage?.role === "assistant") {
|
||||
lastMessage.content = content;
|
||||
lastMessage.format = response?.format;
|
||||
console.log("Message updated:", {
|
||||
role: "assistant",
|
||||
format: lastMessage.format,
|
||||
});
|
||||
} else {
|
||||
newMessages.push({
|
||||
role: "assistant",
|
||||
content,
|
||||
format: response?.format,
|
||||
});
|
||||
}
|
||||
|
||||
if (lastMessage?.role === 'assistant') {
|
||||
lastMessage.content = content;
|
||||
lastMessage.format = response?.format;
|
||||
console.log('Message updated:', {
|
||||
role: 'assistant',
|
||||
format: lastMessage.format
|
||||
});
|
||||
} else {
|
||||
newMessages.push({
|
||||
role: 'assistant',
|
||||
content,
|
||||
format: response?.format
|
||||
});
|
||||
}
|
||||
return newMessages;
|
||||
});
|
||||
},
|
||||
(error) => {
|
||||
handleError(error);
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
return newMessages;
|
||||
});
|
||||
},
|
||||
(error) => {
|
||||
handleError(error);
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
streamingStore.set(false);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
handleError(error);
|
||||
} else {
|
||||
handleError(String(error));
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
streamingStore.set(false);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
handleError(error);
|
||||
} else {
|
||||
handleError(String(error));
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
// Re-export types for convenience
|
||||
|
||||
@@ -1,13 +1,14 @@
|
||||
import { writable } from 'svelte/store';
|
||||
import { browser } from '$app/environment';
|
||||
|
||||
// Load favorites from localStorage if available
|
||||
const storedFavorites = typeof localStorage !== 'undefined'
|
||||
const storedFavorites = browser
|
||||
? JSON.parse(localStorage.getItem('favoritePatterns') || '[]')
|
||||
: [];
|
||||
|
||||
const createFavoritesStore = () => {
|
||||
const { subscribe, set, update } = writable<string[]>(storedFavorites);
|
||||
|
||||
|
||||
return {
|
||||
subscribe,
|
||||
toggleFavorite: (patternName: string) => {
|
||||
@@ -17,7 +18,7 @@ const createFavoritesStore = () => {
|
||||
: [...favorites, patternName];
|
||||
|
||||
// Save to localStorage
|
||||
if (typeof localStorage !== 'undefined') {
|
||||
if (browser) {
|
||||
localStorage.setItem('favoritePatterns', JSON.stringify(newFavorites));
|
||||
}
|
||||
|
||||
@@ -26,11 +27,11 @@ const createFavoritesStore = () => {
|
||||
},
|
||||
reset: () => {
|
||||
set([]);
|
||||
if (typeof localStorage !== 'undefined') {
|
||||
if (browser) {
|
||||
localStorage.removeItem('favoritePatterns');
|
||||
}
|
||||
}
|
||||
};
|
||||
};
|
||||
|
||||
export const favorites = createFavoritesStore();
|
||||
export const favorites = createFavoritesStore();
|
||||
|
||||
@@ -1924,6 +1924,14 @@
|
||||
"tags": [
|
||||
"VISUALIZE"
|
||||
]
|
||||
},
|
||||
{
|
||||
"patternName": "concall_summary",
|
||||
"description": "Extract strategic insights from earnings transcripts for investors.",
|
||||
"tags": [
|
||||
"SUMMARIZE",
|
||||
"BUSINESS"
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user